PATENT CLAIM ANALYSIS

Application Number: 15888705
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-08
Patent Classification: ["725", "070000"]

Abstract:
Methods and systems are provided for using priori knowledge of noise in controlling signal receivers. In a signal receiver, one or more adjustments, relating to generating output signals via the signal receiver, may be determined, with the adjustments directed to one or more particular components of the output signals. When applying the adjustments is determined to cause undesired effects on one or more other components of the output signals, with these other components being intended to remain unchanged when the adjustments are applied, operations of the signal receiver may be controlled based on the undesired effects, with the controlling including mitigating at least some of the effects on the one or more other components of the signals when the one or more adjustments are applied. The adjustments may include frequency re-assignment. The undesired effects may include one or more of amplitude glitches, phase glitches, bit or packet errors, etc.

Claim (Index 28):
The method of  claim 21 , comprising:\n determining when said undesired effects comprise bit or packet errors caused by applying said one or more adjustments; and modifying or changing error handling related functions based on said determination.

Metadata:
- Claim Count in Document: 56.0
- Percentile: 88.0
- Lexical Diversity: 2.27778
- Patent Class: 725.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['13916130', '15478713', '13887314', '15707788', '14595896']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3985818676199448
- 35 USC 102 Novelty (BERT): 0.489764512442633
- Combined Prediction Score: 0.4077001321022137
- Mean Citation Score: 122.301936
- Max Citation Score: 201.07469
- Similarity Product: 139.1411989310944

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