Two-dimensional recursive filter design method based on P system and collaborative optimization strategy

Through the P system and the algorithm of collaborative optimization strategy (PHOA) combined with cross-mutation and cosine enhancement operator, the problem of local optimality in IIR filter design is solved, and the global optimization and stability of the two-dimensional recursive filter is achieved.

CN120409387APending Publication Date: 2025-08-01NANJING TECH UNIV
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Patent Information

Application Number
CN202510472378.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-15
Publication Date
2025-08-01

AI Technical Summary

Technical Problem

The traditional gradient-based IIR filter design method is prone to fall into local optimal solutions when dealing with nonlinear and multimodal error surfaces, and it is difficult to find global optimal solutions. Existing heuristics and evolutionary optimization algorithms such as GA, PSO, and DE also have local optimal problems.

Method used

An improved P system and a co-optimization strategy algorithm (PHOA) is used, combining hybrid membrane structure, cross-mutation operator and cosine enhancement operator, for two-dimensional recursive filter design. Through the combination of global search and local exploration, the filter parameters are optimized to approximate the ideal amplitude response.

Benefits of technology

The designed two-dimensional recursive filter amplitude response is closer to the ideal response and ensures the stability of the filter, which is better than traditional methods.

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Abstract

The invention belongs to the field of circuits and systems, and particularly relates to a two-dimensional recursive filter design method based on a P system and a collaborative optimization strategy, which comprises the following steps of: 1) establishing a model by performing mathematical analysis on a transfer function of a two-dimensional recursive filter; 2) combining a crossover mutation operator which is strong in global search capability but is easy to fall into local optimum, a cosine enhancement operator which is strong in local search capability but is slightly insufficient in population diversity mining, and a mixed membrane structure of a P system into a novel mixed operator capable of balancing convergence and diversity; 3) embedding an object updating rule represented by the operator into a P system with a mixed membrane structure to form a novel P system optimization algorithm (PHOA); 4) taking a numerical value combination of objects in the object set of the novel P system optimization algorithm as a model parameter group of a two-dimensional recursive filter, substituting the model parameter group into the two-dimensional recursive filter model, and calculating an error function between a two-dimensional recursive filter model parameter amplitude response M (omega1, omega2) and an ideal two-dimensional filter amplitude response Md (omega1, omega2); and 5) by minimizing the objective function, obtaining a parameter set and combining the parameter set with a filter model structure to form an optimal two-dimensional recursive digital filter meeting conditions. According to the scheme, the stability of the filter can be ensured, and compared with the previous scheme, the amplitude response of the two-dimensional recursive digital filter is closer to that of an ideal two-dimensional recursive digital filter.
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