Name
Abstract | ||
|---|---|---|
Analog adaptive filters with digitally programmable coefficients can provide speed, power, and area advantages over digital adaptive filters while overcoming the de offset problems associated with fully analog implementations. However, digital estimates of the filter states and gradient signals must be generated from the filter output in order to perform LMS adaptation. State observers studied in the control literature either require access to the system input or require the system to be minimum phase. Here, approximate time-delayed state estimates are obtained from the filter output by truncating a Taylor series expansion of the inverted nonminimum phase zeros. Simulation results are presented for a 5-tap FIR filter, No steady-state error is introduced by de and gain offsets. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/ISCAS.1999.778783 | ISCAS '99: PROCEEDINGS OF THE 1999 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL 3: ANALOG AND DIGITAL SIGNAL PROCESSING |
Keywords | Field | DocType |
taylor series expansion,digital filters,poles and zeros,adaptive filters,control systems,series mathematics,signal generators,adaptive filter,taylor series,finite impulse response filter,fir filter,least squares approximation,fir filters,steady state,state observer | Active filter,Digital filter,Half-band filter,Computer science,Prototype filter,Control theory,Network synthesis filters,2D Filters,Electronic engineering,Adaptive filter,Kernel adaptive filter | Conference |
Citations | PageRank | References |
3 | 0.46 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anthony Chan Carusone | 1 | 269 | 42.19 |
| David A. Johns | 2 | 116 | 26.91 |