# IET Signal Processing

IET Signal Processing > 2017 > 11 > 1 > 104 - 114

IET Signal Processing > 2017 > 11 > 1 > 66 - 72

IET Signal Processing > 2017 > 11 > 1 > 115 - 122

IET Signal Processing > 2017 > 11 > 1 > 36 - 42

IET Signal Processing > 2017 > 11 > 1 > 51 - 58

IET Signal Processing > 2017 > 11 > 1 > 43 - 50

IET Signal Processing > 2017 > 11 > 1 > 95 - 103

IET Signal Processing > 2017 > 11 > 1 > 17 - 25

IET Signal Processing > 2017 > 11 > 1 > 1 - 9

IET Signal Processing > 2017 > 11 > 1 > 73 - 79

IET Signal Processing > 2017 > 11 > 1 > 10 - 16

IET Signal Processing > 2017 > 11 > 1 > 86 - 94

*l*

_{0}-norm penalised shrinkage linear least mean squares (

*l*

_{0}-SH-LMS) algorithm and an

*l*

_{0}-norm penalised shrinkage widely linear least mean squares (

*l*

_{0}-SH-WL-LMS) algorithm for sparse system identification. The proposed algorithms exploit the

*priori*and the

*posteriori*errors to calculate the varying step-size, thus they can adapt to the time-varying channel. Meanwhile,...

IET Signal Processing > 2017 > 11 > 1 > 26 - 35

*L*

_{1}-error fitness function using the bat algorithm (BA) are proposed. The coefficients of numerator and denominator of the differentiators are computed by minimising the

*L*

_{1}-norm of the error fitness function along with imposing the constraint for the location of poles...

IET Signal Processing > 2017 > 11 > 1 > 80 - 85

IET Signal Processing > 2017 > 11 > 2 > 155 - 164

IET Signal Processing > 2017 > 11 > 2 > 181 - 196

IET Signal Processing > 2017 > 11 > 2 > 228 - 237

IET Signal Processing > 2017 > 11 > 2 > 171 - 180

IET Signal Processing > 2017 > 11 > 2 > 213 - 220

IET Signal Processing > 2017 > 11 > 2 > 197 - 204