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 1):
A method of training at least one machine-learning network to classify radio frequency (RF) signals, the method performed by at least one processor executing instructions stored on at least one computer memory coupled to the at least one processor, the method comprising:\n determining an RF signal that is configured to be transmitted through an RF band of a communication medium; determining first classification information associated with the RF signal, the first classification information comprising a representation of at least one 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 that was associated with the RF signal; and updating the at least one machine-learning network 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: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15961454', '15955485', '15688678', '15894774', '15938983']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3724057576910889
- 35 USC 102 Novelty (BERT): 0.5072225531479646
- Combined Prediction Score: 0.3858874372367765
- Mean Citation Score: 209.449794
- Max Citation Score: 305.38593
- Similarity Product: 254.1075653207981

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