In this paper, a design method for the infinite impulse response (IIR) filters using the particle swarm optimization (PSO) is developed. It is well-known that the updating in the PSO tends to stagnate around local minimums due to a strong search directivity. Recently, the asynchronous digenetic PSO with nonlinear dissipative term (N-AD-PSO) has been proposed as a purpose for a diverse search. Therefore, it can be expected that the stagnation can be avoided by the N-AD-PSO. However, there is no report that the N-AD-PSO has been applied to any realistic problems. In this paper, the N-AD-PSO is applied for the IIR filter design. Several examples are shown to clarify the effectiveness and the drawback of the proposed method.

In this paper, a novel method for an effective allocation of non-zero digits in design of CSD (Canonic Signed-Digit) coefficient FIR (Finite Impulse Response) filters is proposed. The design problem can be formulated as a mixed integer programming problem, which is well-known as a NP-hard problem. Recently, a heuristic approach using the PSO (Particle Swarm Optimization) for solving the problem has been proposed, in which the maximum number of non-zero digits was limited in each coefficient. On the other hand, the maximum number of non-zero digits is limited in total in the proposed method and 0-1PSO is applied. It enables an effective allocation of non-zero digits, and provides a good design. Several examples are shown to present the efficiency of the proposed method.

In this paper, we propose a novel method for the design of CSD (Canonic Signed Digit) coefficient FIR (Finite Impulse Response) filters based on ACO (Ant Colony Optimization). This design problem is formulated as a combinatorial optimization problem and requires high computation time to obtain the optimal solution. Therefore, we propose an ACO approach for the design of CSD coefficient FIR filters. ACO is one of the promising approaches and appropriate for solving a combinatorial optimization problem in reasonable computation time. Several design examples showed the effectiveness of our method.

In this paper, we propose a method for designing finite impulse response (FIR) filters with canonic signed digit (CSD) coefficients using particle swarm optimization (PSO). In such a design problem, a large number of local minimums appear in an evaluation function for the optimization. An updating procedure of PSO tends to stagnate around such local minimums and thus indicates a premature convergence property. Therefore, a new framework for avoiding such a situation is proposed, in which the evaluation function is modified around the stagnation point. Several design examples are shown to present the effectiveness of the proposed method.

In this paper, we study a novel method to avoid a local minimum stagnation in the design problem of IIR (Infinite Impulse Response) filters using PSO (Particle Swarm Optimization). Although PSO is appropriate to solve nonlinear optimization problems, it is reported that a local minimum stagnation occurs due to a strong intensification of particles during the search. Then, multi-swarm PSO based on the particle reallocation strategy is proposed to avoid the local minimum stagnation. In this method, a reallocation space is determined by using some global bests. In this paper, the relationship between the number of swarms and the best value of design error is shown and the effectiveness of the proposed method is shown through several design examples.