A Course in Digital Signal Processing
A Course in Digital Signal Processing
Fast and stable least-squares approach for the design of linearphase FIR filters
IEEE Transactions on Signal Processing
Automatic design of frequency sampling filters by hybrid geneticalgorithm techniques
IEEE Transactions on Signal Processing
Peak-constrained least-squares optimization
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
An L1-Method for the Design of Linear-Phase FIR Digital Filters
IEEE Transactions on Signal Processing
Constrained least square design of FIR filters without specifiedtransition bands
IEEE Transactions on Signal Processing
Least squared error FIR filter design with transition bands
IEEE Transactions on Signal Processing
| Hi-index | 0.08 |
This paper considers a new method for FIR filters design. The method uses an L"~ optimality norm. To achieve a better approximating effect, a new modulating function which compresses the oscillations of the cosine is proposed. A parameter sets the gradient of the modulating function, with respect to the oscillations' compression. The approximating polynomial is carried out using Remez' exchange algorithm. An optimal polynomial with lowest possible (four) degree, that approximates an ideal filter's response with high precision is proposed. With the proposed method a FIR filter with arbitrary specifications can be designed. Design examples of FIR filters with a minimization of calculation are performed. The obtained filter's responses are close to the ideal response. The design examples demonstrate that the proposed approach may be a good alternative in several applications.