PATENT CLAIM ANALYSIS

Application Number: 16406205
Application Type: Utility
Filing Date: 2019-05
Publication Date: 2019-08
Patent Classification: ["345", "174000"]

Abstract:
A touch screen controller includes drive circuitry driving force lines with a force signal in a touch data sensing mode and not driving the force lines in a noise sensing mode, sense circuitry sensing touch data at the sense lines in the touch data sensing mode and sensing noise data at the sense lines during the noise sensing mode. Processing circuitry: a) samples the noise data, b) performs trigonometric manipulations of the noise data to produce imaginary noise data and real noise data, and c) determines a noise magnitude value of the noise data as a function of the imaginary noise data and the real noise data. In the noise sensing mode, (a)-(c) are performed for each of a plurality of possible sampling frequencies to be used in the touch data sensing mode in order to determine which sampling frequency is to be used in the touch data sensing mode.

Claim (Index 17):
The touch screen controller of  claim 13 , wherein the processing circuitry is also configured to, for each frame, during a touch data sensing sub-frame, perform steps of:\n sampling the data at a sampling frequency; performing trigonometric manipulations of the data sampled at each of the plurality of different possible sampling frequencies to produce imaginary and real noise data for each of the plurality of different possible sampling frequencies; and determining a touch magnitude value of the data as a function of the plurality of different possible sampling frequencies.

Metadata:
- Claim Count in Document: 41.0
- Percentile: 100.0
- Lexical Diversity: 2.65079
- Patent Class: 345.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15873973', '13887373', '15235974', '13788100', '11619584']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6926319880816828
- 35 USC 102 Novelty (BERT): 0.5517649370808874
- Combined Prediction Score: 0.6785452829816033
- Mean Citation Score: 256.286936
- Max Citation Score: 428.79532
- Similarity Product: 309.33106219251164

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

Dataset: test