PATENT CLAIM ANALYSIS

Application Number: 16068016
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2019-01
Patent Classification: ["341", "051000"]

Abstract:
A signal encoder divides the signal into segments and uses prediction models to approximate the samples of each segment Each local prediction model, each applicable to one segment, is applied in its own translated axis system within the segment and the offset is given by the last predicted value for the previous segment. When the signal is reasonably continuous, it alleviates the need to parameterize the offset for each local predictor model as each local predictor model can build on this last predicted sample value of the previous segment. The encoder as a consequence doesn't suffer from a build up of error even though the offset is not transmitted but instead the last predicted value of the last sample of the previous segment is used. Prediction errors are obtained for the approximated samples and transmitted to the decoder, together with the predictor model parameters and seed value to allow accurate reconstruction of the signal by the decoder.

Claim (Index 1):
A signal encoder\n comprising an input for receiving a signal comprising frames, each frame comprising sequential samples, and an output for providing an encoded signal, the signal encoder further comprising:\n a segmenter comprising an input for receiving the signal and being arranged for segmenting the sequential samples of a frame into segments comprising n sequential samples, \n an approximator comprising an input for receiving segments from the segmenter and seed values and an output for providing an encoded signal comprising for each segment a set of predictor model parameters to the output of the encoder, \n the approximator being arranged to predict samples of a first segment starting from a first seed sample having a first seed value and determine a first set of predictor model parameters by approximating the n sequential samples of the first segment using a first predictor model and subsequently to predict samples of a second segment, subsequent to the first segment, starting from a second seed sample having a second seed value and determine a second set of predictor model parameters by predicting the n sequential samples of the second segment using a second predictor model, characterized in that the second seed value equals an predicted value of a last sample n of the first segment

Metadata:
- Claim Count in Document: 50.0
- Percentile: 95.0
- Lexical Diversity: 1.97619
- Patent Class: 341.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15933108', '14781219', '12671631', '09853883', '14655037']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5340116442417905
- 35 USC 102 Novelty (BERT): 0.4981735995464867
- Combined Prediction Score: 0.5304278397722602
- Mean Citation Score: 199.5742
- Max Citation Score: 206.31525
- Similarity Product: 150.34307494626938

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

Dataset: test