PATENT CLAIM ANALYSIS

Application Number: 15961454
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-11
Patent Classification: ["706", "012000"]

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned compact representations of radio frequency (RF) signals. One of the methods includes: determining a first RF signal to be compressed; using an encoder machine-learning network to process the first RF signal and generate a compressed signal; calculating a measure of compression in the compressed signal; using a decoder machine-learning network to process the compressed signal and generate a second RF signal that represents a reconstruction of the first RF signal; calculating a measure of distance between the second RF signal and the first RF signal; and updating at least one of the encoder machine-learning network or the decoder machine-learning network based on (i) the measure of distance between the second RF signal and the first RF signal, and (ii) the measure of compression in the compressed signal.

Claim (Index 29):
The system of  claim 26 , wherein the operations further comprise:\n determining a measure of distance between the second RF signal and the first RF signal; and based on the measure of distance between the second RF signal and the first RF signal exceeding a threshold, determining an occurrence of an error or an anomaly.

Metadata:
- Claim Count in Document: 10.0
- Percentile: 91.0
- Lexical Diversity: 2.50769
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15961465', '13476862', '15424711', '13343636', '15782725']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3472355972575805
- 35 USC 102 Novelty (BERT): 0.5168785856201917
- Combined Prediction Score: 0.3641998960938417
- Mean Citation Score: 193.806652
- Max Citation Score: 276.59918
- Similarity Product: 184.27618855155228

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

Dataset: test