DETAILED ACTION
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 .
This action is responsive to the original application filed on December 6th, 2022
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. CN2022111668957, filed on September 23rd, 2022.
Specification
The abstract of the disclosure is objected to because it is too long and contains more than 150 words. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words in length. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details.
The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” etc. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided.
Claim Rejections - 35 USC § 112
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 1, 3, 5, 8 and 9 rejected under 35 U.S.C. 112(b), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 1 recites the limitation, “S1, acquiring a WBFM sample signal within a RML 2016.10a data set, and selecting a proper threshold γ to separate a WBFM signal during a silence period;” (Emphasis added). The term “WBFM” in this limitation is not specified or explained and it is unclear to if the applicant is referencing a “Wideband Frequency Modulation” signal or a variable called “WBFM”. Therefore, this claim is rejected under 35 U.S.C. 112(b) for being indefinite. For examination purposes, the limitation, “S1, acquiring a WBFM sample signal within a RML 2016.10a data set, and selecting a proper threshold γ to separate a WBFM signal during a silence period;” will be interpreted to mean, “S1, acquiring a Wideband Frequency Modulation, WBFM, sample signal …”. Appropriate action is required.
Claim 1 further recites, “S5, building a multi-channel feature fusion network model composed of an LSTM network and an FPN network;” (Emphasis added). The term “FPN” in this limitation is not specified or defined in the claim. It is unclear what “FPN” is and if it is the acronym for a “Feature Pyramid Network” or another type of network. Therefore, this claim is rejected under 35 U.S.C. 112(b) for being indefinite. For examination purposes, the limitation, “S5, building a multi-channel feature fusion network model composed of an LSTM network and an FPN network;” will be interpreted to mean, “… an LSTM network and an FPN, Feature Pyramid Network;”. Appropriate action is required.
Claim 3 recites the limitation, “the modulation mode of said RML 2016.1Oa data set being I/Q modulation, enabling a single sample signal to be represented as
x
i
=
I
,
Q
;” (Emphasis added). The variables, “I” and “Q” are not explicitly defined in the claim and it is unclear to what exactly “I” and “Q” pertain to. Therefore, this claim is rejected under 35 U.S.C. 112(b) for being indefinite. For examination purposes, the limitation, the modulation mode of said RML 2016.1Oa data set being I/Q modulation, enabling a single sample signal to be represented as
x
i
=
I
,
Q
;” will be interpreted to mean, “… enabling a single sample signal to be represented as
x
i
=
I
,
Q
, where I represents the in-phase signal and Q represents the quadrature waveform;” Appropriate action is required.
Claim 5 recites the limitation, “a phase calculation formula being as follows:
φ
1
=
a
r
c
t
a
n
Q
i
I
i
wherein arctan is an arctangent function;” (Emphasis added). The variable
φ
1
listed in this limitation is undefined and it is unclear as to what
φ
1
pertains too. Therefore, this claim is rejected under 35 U.S.C. 112(b) for being indefinite. For examination purposes, the limitation, “a phase calculation formula being as follows:
φ
1
=
a
r
c
t
a
n
Q
i
I
i
wherein arctan is an arctangent function;” will be interpreted to mean, “…
φ
1
=
a
r
c
t
a
n
Q
i
I
i
wherein arctan is an arctangent function and
φ
1
is the result of the phase calculation;” appropriate action is required.
Claim 8 recites the limitation, “wherein said LSTM network model further includes a forget gate, an input gate, an output gate and output memory information; the calculation formula of said forget gate is as follows:
f
τ
=
σ
W
f
⋅
h
τ
-
1
,
x
τ
+
b
f
where
W
f
represents a forget gate weight matrix,
x
t
represents an input matrix at a time step length
τ
,
h
τ
-
1
represents an output of a hidden layer at a previous time;
b
f
represents a forget gate deviation; sigmoid function is
σ
x
=
1
1
+
e
-
x
,
f
τ
∈
0,1
, with e as a natural constant;” (Emphasis added). The variable “
σ
” is used multiple times in the limitation and it is unclear if it relates to the sigmoid function only or if it used to denote another calculation. It is unclear what
σ
is explicitly used for and/or if it is another equation or value all together. Therefore, this claim is rejected under 35 U.S.C. 112(b) for being indefinite. For examination purposes, the limitation, “wherein said LSTM network model further includes a forget gate, an input gate, an output gate and output memory information; the calculation formula of said forget gate is as follows:
f
τ
=
σ
W
f
⋅
h
τ
-
1
,
x
τ
+
b
f
where
W
f
represents a forget gate weight matrix,
x
t
represents an input matrix at a time step length
τ
,
h
τ
-
1
represents an output of a hidden layer at a previous time;
b
f
represents a forget gate deviation; sigmoid function is
σ
x
=
1
1
+
e
-
x
,
f
τ
∈
0,1
, with e as a natural constant;” will be interpreted to mean, “… forget gate is as follows:
f
τ
=
σ
W
f
⋅
h
τ
-
1
,
x
τ
+
b
f
where
σ
is equal to a given value, …”. Appropriate action is required.
Claim 8 further recites the limitation, “the calculation formula of said input gate is as follows:
i
s
=
σ
W
i
⋅
h
τ
-
1
,
x
τ
+
b
i
where
W
i
represents an input gate weight matrix,
b
i
represents an input gate deviation,
i
τ
∈
0,1
;” (Emphasis added). The variable “
σ
” is used multiple times in the limitation and it is unclear if it relates to the sigmoid function only or if it used to denote another calculation. It is unclear what
σ
is explicitly used for and/or if it is another equation or value all together. Therefore, this claim is rejected under 35 U.S.C. 112(b) for being indefinite. For examination purposes, the limitation, “the calculation formula of said input gate is as follows:
i
s
=
σ
W
i
⋅
h
τ
-
1
,
x
τ
+
b
i
where
W
i
represents an input gate weight matrix,
b
i
represents an input gate deviation,
i
τ
∈
0,1
;”, will be interpreted to mean, “… input gate is as follows:
i
s
=
σ
W
i
⋅
h
τ
-
1
,
x
τ
+
b
i
where
σ
is equal to a given value, …”. Appropriate action is required.
Claim 8 further recites the limitation, “the calculation formula of said output gate is as follows:
O
τ
=
σ
W
o
⋅
h
τ
-
1
,
x
τ
+
b
o
wherein
W
o
, represents an input gate weight matrix,
b
o
represents an output gate deviation
o
τ
∈
0,1
;” (Emphasis added). The variable “
σ
” is used multiple times in the limitation and it is unclear if it relates to the sigmoid function only or if it used to denote another calculation. It is unclear what
σ
is explicitly used for and/or if it is another equation or value all together. Therefore, this claim is rejected under 35 U.S.C. 112(b) for being indefinite. For examination purposes, the limitation, , “the calculation formula of said output gate is as follows:
O
τ
=
σ
W
o
⋅
h
τ
-
1
,
x
τ
+
b
o
wherein
W
o
, represents an input gate weight matrix,
b
o
represents an output gate deviation
o
τ
∈
0,1
;” will be interpreted to mean, “… output gate is as follows:
O
τ
=
σ
W
o
⋅
h
τ
-
1
,
x
τ
+
b
o
where
σ
is equal to a given value, …”. Appropriate action is required.
Claim 8 further recites the limitation, “the calculation formula of said output memory information is as follows:
C
τ
=
f
τ
*
C
τ
-
1
+
i
ζ
*
t
a
n
h
W
Q
⋅
h
τ
-
1
,
x
ζ
+
b
Q
wherein
W
Q
represents a memory unit weight matrix,
b
Q
represents a memory unit deviation, a hidden output at a time
τ
is
h
τ
=
o
τ
t
a
n
h
C
τ
, with tanh as a hyperbolic tangent function.” (Emphasis added). The variables, “f”, “i”, “Q”, “x” and “
ζ
” are not defined in the claim or in the specification. It is unclear what these variables pertain to and how they are used in the equation. Therefore, this claim is rejected under 35 U.S.C. 112(b) for being indefinite. For examination purposes, the limitation, “the calculation formula of said output memory information is as follows:
C
τ
=
f
τ
*
C
τ
-
1
+
i
ζ
*
t
a
n
h
W
Q
⋅
h
τ
-
1
,
x
ζ
+
b
Q
wherein
W
Q
represents a memory unit weight matrix,
b
Q
represents a memory unit deviation, a hidden output at a time
τ
is
h
τ
=
o
τ
t
a
n
h
C
τ
, with tanh as a hyperbolic tangent function.” Will be interpreted to mean, “… output memory information is as follows:
C
τ
=
f
τ
*
C
τ
-
1
+
i
ζ
*
t
a
n
h
W
Q
⋅
h
τ
-
1
,
x
ζ
+
b
Q
where
f
τ
is a given value at time or step
τ
, i is a given value, Q is a given value, x is a given value, and
ζ
represents a step or a given value, …” Appropriate action is required.
Claim 9 recites the limitation, “in a deep learning training process, an optimizer being set to be Adam, a loss function being a cross entropy function, adopting a dynamic learning rate scheme with an initial learning rate set to 0.001;” (Emphasis added). The statement “an optimizer being set to be Adam” is unclear because the limitation states it sets an optimizer to an arbitrary variable called “Adam”. The variable “Adam” is not clearly introduced or defined in claim and it unclear to what “Adam” is. In machine learning there is an optimizer called an “Adam optimizer”, which perform optimization functions similar to those disclosed in claim 9. Both of the prior arts listed below, see 103 rejection, claim 9, disclose using an “Adam Optimizer”. It is unclear with the language of this claim to determine if the “Adam” represents a value or set of values or is the function called “Adam Optimizer”. Therefore, this claim is rejected under 35 U.S.C. 112(b) for being indefinite. For examination purposes, the limitation, “in a deep learning training process, an optimizer being set to be Adam, a loss function being a cross entropy function, adopting a dynamic learning rate scheme with an initial learning rate set to 0.001;” will be interpreted to mean, “… training process, an Adam optimizer will be, a loss function…”. Appropriate action is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-10 are rejected under 35 U.S.C 101 because the claimed invention is
directed to an abstract idea without significantly more. The analysis of the claims will
follow the 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50
(“2019 PEG”).
Claim 1
Step 1 – Is the claim to a process, machine, manufacture or composition of matter?
Claim 1, recites “An automatic modulation classification method based on deep learning network fusion, comprising the following steps:” therefore it is directed to the statutory category of a process.
Step 2A Prong 1 – Does the claim recite an abstract idea, law of nature, or natural
phenomenon?
The claim recites, inter alia:
“S1, acquiring a WBFM sample signal within a RML 2016.10a data set, and selecting a proper threshold
γ
to separate a WBFM signal during a silence period;” Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of evaluating and observing data, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper. The limitation is merely applying an abstract idea on generic computer system. See MPEP 2106.04(a)(2)(III)(c).
“S2, expanding a new WBFM signal to 1000 by adopting a data enhancement method, and expanding an original data set;” Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of evaluating and observing data, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper. The