Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
This action is in response to the amendment and remarks filed 1/29/26.
Claims 1-20 are pending.
Applicant's arguments filed 1/29/26 have been fully considered but they are not persuasive.
In response to applicants arguments that the claims shouldn’t be interpreted under 35 USC 112(f) because no place holder is used in the instant claims
As seen in the rejection, generic placeholders are highlighted below:
Claim 17, “a compact support neuron (CSN) module configured to generate a CSN using a radial basis function (RBF) neuron defined by a radial function centered at a parameter vector, μ, such that an output of the RBF neuron is zero outside a sphere of a radius, R, at μ”
Claim 17, “a compact support neural network (CSNN) module configured to generate a CSNN using the CSN”
Claim 17, “a training module configured to train the CSNN”
Claim 17, “a normalization module configured to normalize the CSNN”
Claim 18, “a pruning module configured to prune a dead neuron from the CSNN”
In response to applicants arguments that the claims 17-20 comply with the written description requirement for lacking structure in the specification, the specification merely recites the claim language and there are no algorithms disclosed for performing the claimed functions.
In response to applicants arguments that claims are directed to statutory subject matter under 35 USC 101, see new grounds of rejections due to amended claims below.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are in:
Claim 17, “a compact support neuron (CSN) module configured to generate a CSN using a radial basis function (RBF) neuron defined by a radial function centered at a parameter vector, μ, such that an output of the RBF neuron is zero outside a sphere of a radius, R, at μ”
Claim 17, “a compact support neural network (CSNN) module configured to generate a CSNN using the CSN”
Claim 17, “a training module configured to train the CSNN”
Claim 17, “a normalization module configured to normalize the CSNN”
Claim 18, “a pruning module configured to prune a dead neuron from the CSNN”
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 17-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding Claims 17-20:
The disclosure does not provide adequate structure to perform the claimed functions of:
Claim 17, “a compact support neuron (CSN) module configured to generate a CSN using a radial basis function (RBF) neuron defined by a radial function centered at a parameter vector, μ, such that an output of the RBF neuron is zero outside a sphere of a radius, R, at μ”
Claim 17, “a compact support neural network (CSNN) module configured to generate a CSNN using the CSN”
Claim 17, “a training module configured to train the CSNN…”
Claim 17, “a normalization module configured to normalize the CSNN”
Claims 18-20 are rejected for inheriting the deficiencies of claim 17.
Claim 18, “a pruning module configured to prune a dead neuron from the CSNN…”
The specification merely recites the claim language and there are no algorithms disclosed for performing the claimed functions. Therefore, the specification does not demonstrate that the applicant has made an invention that achieves the claimed functions because the invention is not described with sufficient detail that one of ordinary skill in the art can reasonably conclude that the inventor had possession of the claimed invention.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 17-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claims 17-20:
Claims 17-18 include claim limitations that invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The claim limitations:
Claim 17, “a compact support neuron (CSN) module configured to generate a CSN using a radial basis function (RBF) neuron defined by a radial function centered at a parameter vector, μ, such that an output of the RBF neuron is zero outside a sphere of a radius, R, at μ”
Claim 17, “a compact support neural network (CSNN) module configured to generate a CSNN using the CSN”
Claim 17, “a training module configured to train the CSNN…”
Claim 17, “a normalization module configured to normalize the CSNN….”
Claim 18, “a pruning module configured to prune a dead neuron from the CSNN…”
The specification is devoid of adequate structure to perform the claimed functions. The specification merely recites the claim language. There is no disclosure of any particular structure, either explicitly or inherently, to perform the claimed functions. As would be recognized by those of ordinary skill in the art, the claimed functions can be performed on a generically recited computer or processor. The specification does not provide sufficient details such that one of ordinary skill in the art would understand which structure or structures perform(s) the claimed functions. Therefore, claims 17-18 are indefinite and are rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. Additionally, dependent claims 18-20 are rejected for inheriting the deficiencies of claim 17.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim Rejections - 35 USC § 101
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step 1: Claims 1-9 are rejected under 35 U.S.C. § 101 because the claimed invention is non-statutory subject matter. The claims recite:
In claim 1: A compact support neural network (CSNN) comprising:
In claims 2-4 and 6-9, The CSNN of claim 1
In claim 5, The CSNN of claim 4
When viewed individually and as a whole, it appears that the claims would be reasonably interpreted by one of ordinary skill as directed to mathematical concepts. As drafted, under their broadest reasonable interpretation (BRI), in view of the specification, the claims are directed to a compact support neural network (CSNN) comprising layers of neurons, and the neurons are disclosed by the instant specification to be directed mathematical concepts (e.g. standard dot product, radial basis function, activation function). Paragraph [0010] of the instant specification describes the neurons: “[p]resented herein is a neuron generalization that has the standard dot-product based neuron and the radial basis function (RBF) neuron as two extreme cases of a shape parameter. Using rectified linear unit (ReLU) as the activation function, a neuron is obtained that has compact support, which means its output is zero outside a bounded domain.” In other words, the claims only recites mathematical concepts and does not recite a process, machine, manufacture, or composition of matter. Therefore, claims 1-9 are rejected under 35 35 U.S.C. § 101 as they are not drawn to eligible subject matter.
Claims 10-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 10-16 are directed to a method [process]. Claims 17-20 are directed to a neural network environment [machine].
Regarding Claim 10:
Step 2A, Prong 1: The following limitations are directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind or with pen and paper (including an observation, evaluation, judgement, or opinion).
A method of generating a neural network, the method comprising
normalizing the CSNN such that inputs have zero mean and a standard deviation 1=<d on training data wherein d is a dimension
As drafted, under their broadest reasonable interpretation (BRI), in view of the specification, the above limitations cover concepts performed in the human mind (observation, evaluation, judgement, or opinion). Given a sufficiently small set of data, nothing in the claim prohibits this process from being performed mentally or with pen and paper.
The following limitations are directed to the abstract idea of a mathematical concept (i.e., mathematical relationships, mathematical formulas or equations, or mathematical calculations) [see MPEP 2106.04(a)(2) I.C.].
obtaining a compact support neuron (CSN) using a radial basis function (RBF) neuron defined by fw(x) = a (R2 - xTx - wTw + 2wTx) = ara(R2 - 2xW - ||wll2 - b) + 2wTx + bi, which is a radial function centered at a parameter vector, p, such that an output of the RBF neuron is zero outside a sphere of a radius, R, at p, wherein x is an input vector to a neuron, w is a weight vector of the neuron, a is a shape parameter, a is an activation function, and b is a bias function
obtaining a compact support neural network (CSNN) using the CSN
Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application.
The following additional element is adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the judicial exception into a practical application.
training the CSNN by first training a regular neural network (a = 0) and then gradually increasing the shape parameter a from 0 towards 1
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception.
The following additional element is adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to amount to significantly more than the judicial exception.
training the CSNN
Regarding Claim 11:
Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 10.
The following limitation is directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgement, or opinion).
pruning a dead neuron from the CSNN that have zero response to the training
As drafted, under their broadest reasonable interpretation (BRI), in view of the specification, the above limitations cover concepts performed in the human mind (observation, evaluation, judgement, or opinion). Given a sufficiently small set of data, nothing in the claim prohibits this process from being performed mentally or with pen and paper.
Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application.
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception.
Regarding Claim 12:
Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 10.
Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein the CSNN comprises: a first layer of neurons
a second layer of neurons, wherein the second layer comprises a plurality of CSNs
an output layer, wherein the second layer is the last layer before the output layer
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein the CSNN comprises: a first layer of neurons
a second layer of neurons, wherein the second layer comprises a plurality of CSNs
an output layer, wherein the second layer is the last layer before the output layer
Regarding Claim 13:
Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 12.
Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein the first layer comprises a convolutional neural network layer or a CSN layer
wherein the second layer comprises only the plurality of CSNs
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein the first layer comprises a convolutional neural network layer or a CSN layer
wherein the second layer comprises only the plurality of CSNs
Regarding Claim 14:
Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 12.
Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein each of the CSNs has a property of compact support and provides an output of zero outside a bounded domain
wherein the output layer provides a zero response or a lowest possible confidence in a region at or beyond a predetermined distance from the training data
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein each of the CSNs has a property of compact support and provides an output of zero outside a bounded domain
wherein the output layer provides a zero response or a lowest possible confidence in a region at or beyond a predetermined distance from the training data
Regarding Claim 15:
Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 12.
Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein the output layer is a linear layer without a bias term
wherein the output layer is configured to provide an output to an autonomous driving application
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein the output layer is a linear layer without a bias term
wherein the output layer is configured to provide an output to an autonomous driving application
Regarding Claim 16:
Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 12.
Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein the second layer is a hidden layer containing the plurality of CSNs
wherein the second layer guarantees that a space where the CSNN has a non-zero response is bounded
wherein the output layer is a standard fully connected layer without bias
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein the second layer is a hidden layer containing the plurality of CSNs
wherein the second layer guarantees that a space where the CSNN has a non-zero response is bounded
wherein the output layer is a standard fully connected layer without bias
Regarding Claim 17:
Step 2A, Prong 1: The following limitation is directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind or with pen and paper (including an observation, evaluation, judgement, or opinion).
normalize the CSN such that inputs have zero mean and a standard deviation 1on training data wherein d is a dimension
As drafted, under their broadest reasonable interpretation (BRI), in view of the specification, the above limitations cover concepts performed in the human mind (observation, evaluation, judgement, or opinion). Given a sufficiently small set of data, nothing in the claim prohibits this process from being performed mentally or with pen and paper.
The following limitations are directed to the abstract idea of a mathematical concept (i.e., mathematical relationships, mathematical formulas or equations, or mathematical calculations) [see MPEP 2106.04(a)(2) I.C.].
generate a CSN using a radial basis function (RBF) neuron defined by fw(x) = a (R2 - xTx - wTw + 2wTx) = aa(R2 - Hx2 - ||wll2 - b) + 2wTx + bi, which is a radial function centered at a parameter vector, p, such that an output of the RBF neuron is zero outside a sphere of a radius, R, at p, wherein x is an input vector to a neuron, w is a weight vector of the neuron, a is a shape parameter, a is an activation function, and b is a bias function
generate a CSNN using the CSN
Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application.
The following additional element is adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the judicial exception into a practical application.
A neural network environment comprising: a computing device
a compact support neuron (CSN) module configured to…
a compact support neural network (CSNN) module configured to…
a training module configured to train the CSNN by first training a regular neural network (a = 0) and then gradually increasing the shape parameter a from 0 towards 1
a normalization module configured to…
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception.
The following additional element is adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to amount to significantly more than the judicial exception.
A neural network environment comprising: a computing device
a compact support neuron (CSN) module configured to…
a compact support neural network (CSNN) module configured to…
a training module configured to train the CSNN by first training a regular neural network (a = 0) and then gradually increasing the shape parameter a from 0 towards 1
a normalization module configured to…
Regarding Claim 18:
Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 17.
The following limitation is directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgement, or opinion).
prune a dead neuron that have zero response to training
As drafted, under their broadest reasonable interpretation (BRI), in view of the specification, the above limitations cover concepts performed in the human mind (observation, evaluation, judgement, or opinion). Given a sufficiently small set of data, nothing in the claim prohibits this process from being performed mentally or with pen and paper.
Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application.
The following additional element is adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the judicial exception into a practical application.
a pruning module configured to…
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception.
The following additional element is adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to amount to significantly more than the judicial exception.
a pruning module configured to…
Regarding Claim 19:
Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 17.
Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein the CSNN comprises: a first layer of neurons
a second layer of neurons, wherein the second layer comprises a plurality of CSNs
an output layer, wherein the second layer is the last layer before the output layer
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein the CSNN comprises: a first layer of neurons
a second layer of neurons, wherein the second layer comprises a plurality of CSNs
an output layer, wherein the second layer is the last layer before the output layer
Regarding Claim 20:
Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 17.
Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein each of the CSNs has a property of compact support and provides an output of zero outside a bounded domain
wherein the output layer provides a zero response or a lowest possible confidence in a region at or beyond a predetermined distance from the training data
Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception.
The following additional elements are directed to intended use, field of use, or technological environment in which to apply a judicial exception [see MPEP 2106.05(h)].
wherein each of the CSNs has a property of compact support and provides an output of zero outside a bounded domain
wherein the output layer provides a zero response or a lowest possible confidence in a region at or beyond a predetermined distance from the training data
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANN J LO whose telephone number is (571)272-9767. The examiner can normally be reached Monday-Friday, 9 AM to 5 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Cordelia Zecher can be reached at 571-272-7771. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ANN J LO/Supervisory Patent Examiner, Art Unit 2159
Prosecution Insights