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利用MATLAB仿真软件对LMS和RLS两种算法进行仿真，通过仿真比较了两种算法的收敛速度，对两种算法收敛后的误码率进行分析，研究了步长对LMS算法均方误差性能曲线的影响和遗忘因子对RLS算法性能曲线的影响。-Using MATLAB simulation software for two types of LMS and RLS algorithm simulation, the simulation compares the convergence rate of two algorithm
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使用LMS算法进行盲多用户检测，并计算出信干比和误码率-LMS algorithm using the blind multi-user detection, and calculate the signal to interference ratio and bit error rate
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Inter-symbol interference if not taken care off may
cause severe error at the receiver and the detection of signal becomes
difficult. An adaptive equalizer employing Recursive Least Squares
algorithm can be a good compensation for the ISI probl
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This paper compares performance of nite impulse
response (FIR) adaptive linear equalizers based on the recursive least-squares (RLS) and least mean square(LMS) algorithms in nonstationary uncorrelated scattering wireless channels. Simulation resul
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运用LMS、RLS、LSL等自适应滤波算法对16QAM信号进行处理，比较其误码率-Use of the LMS, RLS, LSL adaptive filtering algorithm for 16QAM signal processing, to compare the bit error rate
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多径时延信道下的OFDM误码率性能，进行了简单的lms信道估计(OFDM bit error rate performance in multipath delay channels)
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