Transplant and Optimization of CiSSA-CSP Feature Extraction Algorithm on DSP Platform
In order to realize the on-line and real-time processing of portable signal binary classification analysis systems,DSP platform is used to implement the embedded transplantation of CiSSA-DSP feature extraction algorithm.A CiSSA-CSP feature extrac-tion algorithm has the excellent performance of time-frequency-spatial feature extraction,and it is suitable for extracting non-stationa-ry signals in real-time binary classification system.Compared with PC,an embedded implementation has the characteristics of minia-turization,portability,low power consumption and low delay,while the computing resources and memory of embedded platform pro-cessor is limited,and the transplant feature extraction algorithm must be optimized to ensure the binary classification accuracy and low delay.The steps of the CiSSA-CSP algorithm,the compiler optimization,keywords and library functions are optimized to improve the compilation efficiency,the CiSSA-CSP feature extraction algorithm is transplanted to the TMS320C6678 embedded DSP platform,and its effectiveness for real-time classification system is verified by the public dataset.Compared with Matlab on PC,the classification ac-curacy of the binary classification system is reduced by less than 0.5％on the DSP platform,and the computing time for singel experi-ment is less than 0.15s.
binary classificationfeature extractionCiSSA-CSPDSPtransplant and optimization
万方数据
维普
