PATENT CLAIM ANALYSIS

Application Number: 15955426
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2019-10
Patent Classification: ["708", "200000"]

Abstract:
A neural network engine comprises a plurality of floating point multipliers, each having an input connected to an input map value and an input connected to a corresponding kernel value. Pairs of multipliers provide outputs to a tree of nodes, each node of the tree being configured to provide a floating point output corresponding to either: a larger of the inputs of the node; or a sum of the inputs, one output node of the tree providing a first input of an output module, and one of the multipliers providing an output to a second input of the output module. The engine is configured to process either a convolution layer of a neural network, an average pooling layer or a max pooling layer according to the kernel values and whether the nodes and output module are configured to output a larger or a sum of their inputs.

Claim (Index 3):
A neural network engine according to  claim 1  wherein said activation function is defined by a binary slope parameter and a slope coefficient.

Metadata:
- Claim Count in Document: 15.0
- Percentile: 91.0
- Lexical Diversity: 2.66102
- Patent Class: 708.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15234851', '15423292', '15719829', '15600807', '15423289']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4074415528304941
- 35 USC 102 Novelty (BERT): 0.5122121007505678
- Combined Prediction Score: 0.4179186076225014
- Mean Citation Score: 197.769296
- Max Citation Score: 207.22314
- Similarity Product: 131.1099008011937

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test