PATENT CLAIM ANALYSIS

Application Number: 15961465
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-10
Patent Classification: ["706", "012000"]

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned identification of radio frequency (RF) signals. One of the methods includes: determining an RF signal configured to be transmitted through an RF band of a communication medium; determining first classification information that is associated with the RF signal, and that includes a representation of a characteristic of the RF signal or a characteristic of an environment in which the RF signal is communicated; using at least one machine-learning network to process the RF signal and generate second classification information as a prediction of the first classification information; calculating a measure of distance between (i) the second classification information that was generated by the at least one machine-learning network, and (ii) the first classification information associated with the RF signal; and updating the at least one machine-learning network based on the measure of distance.

Claim (Index 24):
The system of  claim 16 , wherein using the at least one machine-learning network to process the RF signal and generate the second classification information further comprises:\n determining, based on the at least one machine-learning network, a first time scale for processing the RF signal; and using the at least one machine-learning network to processes the RF signal based on the first time scale, wherein updating the at least one machine-learning network further comprises updating the first time scale to a second time scale based on the measure of distance between the second classification information and the first classification information.

Metadata:
- Claim Count in Document: 80.0
- Percentile: 91.0
- Lexical Diversity: 2.13924
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15961454', '15955485', '15688678', '15894774', '15938983']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.400051585840154
- 35 USC 102 Novelty (BERT): 0.5136517883251429
- Combined Prediction Score: 0.4114116060886529
- Mean Citation Score: 209.449794
- Max Citation Score: 305.38593
- Similarity Product: 229.6796630119157

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

Dataset: test