PATENT CLAIM ANALYSIS

Application Number: 16038872
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2018-11
Patent Classification: ["706", "025000"]

Abstract:
An apparatus for executing backpropagation of an artificial neural network comprises an instruction caching unit, a controller unit, a direct memory access unit, an interconnection unit, a master computation module, and multiple slave computation modules. For each layer in a multilayer neural network, weighted summation may be performed on input gradient vectors to calculate an output gradient vector of this layer. The output gradient vector may be multiplied by a derivative value of a next-layer activation function on which forward operation is performed, so that a next-layer input gradient vector can be obtained. The input gradient vector may be multiplied by an input neuron counterpoint in forward operation to obtain the gradient of a weight value of this layer, and the weight value of this layer can be updated according to the gradient of the obtained weight value of this layer.

Claim (Index 18):
The method of  claim 15 , further comprising:\n instructing, by the controller unit, the master computation module to perform one of the one or more groups of micro-instructions; and instructing, by the controller unit, the slave computation modules to perform other groups of the micro-instructions.

Metadata:
- Claim Count in Document: 29.0
- Percentile: 95.0
- Lexical Diversity: 2.15493
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['11457601', '11953671', '13781508', '15143293', '13707088']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3119219674348256
- 35 USC 102 Novelty (BERT): 0.5031317381531231
- Combined Prediction Score: 0.3310429445066554
- Mean Citation Score: 167.543166
- Max Citation Score: 176.10582
- Similarity Product: 102.11337789575816

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test