Nlms algorithm for adaptive filter
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The document discusses the NLMS adaptive filter algorithm. The LMS algorithm adjusts the coefficients of a filter to minimize the mean square error between the desired and actual output signals. The NLMS algorithm normalizes the step-size parameter based on the input signal power to overcome issues from changing input power levels. A result is shown comparing actual and estimated filter weights using the NLMS algorithm.
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Nlms algorithm for adaptive filter
- 1. NLMS Algorithm for adaptive filter DSP lab-Mini Project Chintan Joshi
- 2. LMS Filter • Adjusts the coefficients of w(n) of a filter in order to reduce the mean square error between the desired signal and output of the filter. • Algorithm use the gradient vector of the filter tap weights • w(n +1) = w(n) +μe(n)x* (n)
- 3. NLMS Adaptive Filter • In real Scenario, input signal power not remain constant – change the step-size between two adjacent coefficients of the filter will also change – affect the convergence rate – gradient noise amplification problem • To overcome this problem, adjust the step-size parameter with respect to the input signal power • Therefore the step-size parameter is said to be normalized
- 4. NLMS Adaptive Filter cont..
- 5. Result Comparison of the actual weights and the estimated weights 0.5 Actual weights 0.4 Estimated weights 0.3 0.2 0.1 0 -0.1 -0.2 -0.3 -0.4 -0.5 0 1 2 3 4 5 6