Farhang-Boroujeny: Lattice PFBLMS: Fast converging structure for efficient implementation of frequency-domain adaptive filters, Signal Processing , 78 (1), 79–89, October 1999.Chan et al., " Lattice PFBLMS: Fast Converging Structure for Efficient Implementation of Frequency-Domain Adaptive Filters...
The Fast Quasi-Newton algorithm described in this paper has been seen to avoid the performance degradation caused in basic adaptive algorithms by colored input signals. The FQN algorithm offers convergence performance far superior to LMS, and is comparable to RLS in tracking ability. At the same t...
Although numerically robust, the QR-decomposition recursive least- squares (QRD-RLS) algorithms studied in the previous chapter are computationally intensive, requiring a number of mathematical operations in the order of N2, or о[N2], N being the order of the adaptive filter. This chapter describ...
The spectral analysis of signals is currently either dominated by the speed–accuracy trade-off or ignores a signal’s often non-stationary character. Here we introduce an open-source algorithm to calculate the fast continuous wavelet transform (fCWT). T
[2]. Nevertheless, the most important drawbacks of the adaptive filters are the slow convergence speed especially when the length of the finite impulse response (FIR) is selected very large as in teleconferencing and audio-conferencing systems. Also, their implementation will be complicated and ...
fCWT’s accuracy and noise-handling capabilities are not compromised by its highly efficient implementation. Small differences in the time–frequency spectrum can be seen at the edges. However, these differences are caused by MATLAB’s mitigation of edge artifacts (202020Implementation of fCWTsection...
The implementation of doing this is to average the power of FFT for each channel, e.g., Rave2=1N∑n=1N Rn2.(12) Illustratively, N=5 and each channel is initialized with: Rn,int=1Rave2.(13) The use of the square root of the average power in equation (13) further ...
The same method can be applied to the implementation of time-domain block LMS adaptive FIR filters where the weight vector is updated in the transform domain and of frequency-domain block LMS adaptive FIR filters. The method is well suited to implementation on DSP (digital signal processing) ...
Without prewindowing, however, the RLS algorithm becomes computationally more burdensome and more implementation-sensitive. Initialization also perturbs the algorithm. As described in J. M. Cioffi and T. Kailath, “Fast, recursive least squares transversal filters for adaptive filtering”, IEEE Trans....
Fast recursive least squares (RLS) adaptive filters are still too complex for many applications. The authors discuss the fast Newton transversal filters (FNTFs), a new family of fast RLS filters based on prediction order reduction, which can have complexity close to that of LMS. A simple ...