In this paper the concept of the electomyogram EMG and how the surface electomyogram SEMG signal is obtained have been given. Electomyogram system offers a great benefit to the sport filed application. Due to their requirements SEMG systems has been designed and implemented. This system consists of three basic units. These units are: Detection, signal conditioning, and signal processing. It provides measurement of electrical activity of muscles, efficiency of electrical activity, explosion power (response velocity), and fatigue degree. These parameters are most vital to physical assessment in the sports field.
The aim of this paper is to improve the performance of Frequency domain Block Least Mean Square (FBLMS) adaptive algorithm that is used for fading channel estimation. Multistep adaptive algorithm known as Second Order LMS (SOLMS) is used to improve the mobile channel tracking coupled with FBLMS. A one step Least Square (LS) prediction, based on the estimate of the sampled impulse response and the estimate of their speed of variation, is used along with FBLMS. The efficiency of both algorithms is confirmed by simulation test results for moderate(pedestrian) with Doppler frequency offset of 6 Hz and fast varying(vehicular) mobile channels th Doppler frequency offset of 100 Hz. The results show that both methods offer improvement in the Mean Square Estimation Error.
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