PATENT CLAIM ANALYSIS

Application Number: 16132103
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-10
Patent Classification: ["398", "202000"]

Abstract:
A high-speed and high-precision photonic analog-to-digital conversion device capable of realizing intelligent signal processing. Learning ability of deep learning technology is utilized to learn the nonlinear response and channel mismatch effect of the system and configure optimal parameters of the deep network. Deterioration of photonic analog-to-digital conversion system performance caused by nonlinear distortion and channel mismatch distortion is eliminated in real time, and performance indicators thereof are improved. By using the induction and deduction ability of deep learning technology, intelligent signal processing of the input signal is realized, and users are provided with digital signals that meet the requirements. It's important for improving the performance of microwave photonic systems that require high sampling rate, high time precision, and high sampling accuracy, such as microwave photonic radar and optical communication systems, and also critical to improve the signal processing ability of such systems under complex conditions.

Claim (Index 13):
A method for customized intelligent signal processing using the device of  claim 1 , comprising\n in a training phase, inputting customized waveform signals provided by the signal source into the high-speed photonic analog-to-digital conversion system, sampling the customized waveform signals by the high-reputation-rate pulse light source, and sequentially passing the customized waveform signals through the multi-channel demultiplexer module and the parallelization photoelectric conversion module, obtaining sampling results of the customized waveform signals at an output port of the parallelization electronic-quantization module, and treating the sampling results as a first part of a training sample set, generating customized digital signals by the digital signal processor as a second part of the training sample set, combining the first part and the second part of the training sample set by the deep network to train parameters of the deep network, resetting the parameters of the deep network, and establishing a customized calculation model for intelligent signal processing in the deep network; and in an application phase, inputting sampled signals into the high-speed photonic analog-to-digital conversion system by the second input port of the photon sampling gate, sampling the sampled signals by the high-reputation-rate pulse light source, sequentially passing the sampled signals through the multi-channel demultiplexer module and the parallelization photoelectric conversion module to obtain digital signals, inputting the digital signals into the deep network via the parallelization electronic-quantization module, using the customized calculation model in the deep network and performing intelligent signal processing on the digital signals, and outputting digital signals that meet customization requirements.

Metadata:
- Claim Count in Document: 29.0
- Percentile: 97.0
- Lexical Diversity: 1.81609
- Patent Class: 398.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['13990161', '13386422', '14698087', '16006101', '13478255']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6500299502987638
- 35 USC 102 Novelty (BERT): 0.4984910643620912
- Combined Prediction Score: 0.6348760617050965
- Mean Citation Score: 168.974198
- Max Citation Score: 183.94719
- Similarity Product: 131.0774989569032

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