Realization and application of parallel computing in identification of dynamic model
并行计算在动态模式识别中的实现和应用*

The paper introduce a neural network-based learning theory, which is called the deterministic learning theory, and demonstrate the application of the theory in the dynamic pattern recognition. Based on the classical Mansoux compressor model, the deterministic learning theory is applied to the model and the parallel computing for the rapid recognition of compressor model under multi-dynamic patterns is achieved, by using the OpenMP multi-core programming environment and taking the DAWNING server as the hardware platform. It provides an excellent application for the parallel computing in rapid pattern recognition.