No abstract

No abstract

This work presents a formulation of the FIR filter problem with sum of power-of-two (POT) coefficients as a mixed integer linear problem and solves it heuristically. The optimization problem is formulated to minimize the number of nonzero bits in each coefficient without violating the filter specifications within the pass and stop bands. A novel fast and efficient local search optimization algorithm for the filter coefficients is proposed. The algorithm called POTx does not use a tree structure in contrast to conventional MILP algorithms and offers fast computation because of a presorted search space, a monotonic dedicated search space, and the use of abort conditions. The proposed approach achieves comparable reductions to nonheuristic approaches because of a hybrid allocation scheme and multiple optimization iterations. The usefulness of the proposed algorithm for low power design of FIR filters is shown through the evaluation of several benchmark filters.Index Terms-Canonic signed digit (CSD), finite impulse response (FIR), hybrid searching space, low power, mixed integer linear programming (MILP), monotonicity, power-of-two (POT).

By combining the class of feedforward neural networks and results from the wavelet theory, we propose a new class of networks we call wavelet networks to approximate any nonlinear function. Then we propose a stochastic gradient procedure for black-box identification of nonlinear static systems based on this new class of networks. Promising experiments are reported.