Application of BP Neural Network in PSD Nonlinear Correction
| Autor: | Jin Ping Yang, Zhuo Jing Yang, Wen Jie Hao, Jian Wei Zhang |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Engineering
Quantitative Biology::Neurons and Cognition Artificial neural network business.industry Detector Control engineering General Medicine Function (mathematics) Displacement (vector) Nonlinear system Position (vector) Arbitrary-precision arithmetic MATLAB business computer Algorithm computer.programming_language |
| Zdroj: | Applied Mechanics and Materials. :400-404 |
| ISSN: | 1662-7482 |
| DOI: | 10.4028/www.scientific.net/amm.651-653.400 |
| Popis: | Because resistance of two-dimensional position sensitive detector's (PSD) photo surface is not absolute uniformity that its output is nonlinear. It is this feature enables the PSD difficult to measure small displacement. In order to solve this problem, BP neural network is proposed to solve the problem of PSD nonlinear correction after the study of traditional nonlinear correction method; BP neural network would have a strong ability of nonlinear mapping after training, and it can approach arbitrarily contact function by arbitrary precision, and MATLAB neural networking boxes can simulate BP neural network easily. Simulation and verification indicate that the method has a remarkable effect in solving nonlinear problems, and it can meet system requirements. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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