Title :
New FIR adaptive filtering algorithm based on quantized gradients and least-squares convergence factors
Author_Institution :
Dept. of Telecommun., Mahanakom Univ. of Technol., Bankok, Thailand
fDate :
2/1/1999 12:00:00 AM
Abstract :
A new FIR adaptive filtering algorithm, using quantized gradients with a variable convergence factor that minimizes an exponentially weighted sum square error, is proposed. The proposed algorithm converges about as fast as the optimum block adaptive shifting algorithm does. However, when effective reusing data length due to the exponential weighting is a power-of-two number, the proposed algorithm requires a much smaller number of multiplications and divisions
Keywords :
FIR filters; adaptive filters; convergence of numerical methods; errors; filtering theory; least squares approximations; FIR adaptive filtering algorithm; divisions; error minimization; exponentially weighted sum square error; least-squares convergence factors; multiplications; quantized gradients; variable convergence factor; Adaptive filters; Computer errors; Computer simulation; Convergence; Filtering algorithms; Finite impulse response filter; Least squares approximation; Quantization; Signal processing algorithms; Telecommunication computing;
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
