Design of two-dimensional recursive filters by using neural networks

Mladenov, Valeri; Mastorakis, N.E.

doi:10.1109/72.925560

Cited by 49 publications

(91 citation statements)

References 18 publications

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“…In [11], the problem has been tackled using neural networks. In [12] and [13], a binary coded GA and a hybrid GA are attempted to solve this problem.…”

Section: Problem Formulationmentioning

confidence: 99%

“…In [12] and [13], a binary coded GA and a hybrid GA are attempted to solve this problem. It is also been optimized by a quantum-behaved PSO and a modified PSO algorithm in [15] and [16], respectively.…”

Section: Problem Formulationmentioning

confidence: 99%

“…V. M. Mladenov et al used a continuous-time neural network to the design of 2-D recursive filter [11]. N. E. Mastorakis et al proposed a new design method for two-dimensional recursive filters using genetic algorithms [12]. J. T. Tsai et al proposed a hybrid Taguchi-genetic algorithm (HTGA) to solve the design problem of 2-D recursive digital filters and obtained better results than previous design methods [13].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Moreover, two-dimensional filter mathematics can be used in grid methods for solving partial differential equations, distributed control, and iterative learning control, etc. essential practical importance [5], [12], [13].…”

Section: Introductionmentioning

confidence: 99%

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Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm

Wu¹,

Wang²,

Yuan³

2011

IJCIS

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This paper investigates a novel approach to the design of two-dimensional recursive digital filters using differential evolution (DE) algorithm. The design task is reformulated as a constrained minimization problem and is solved by an Self-adaptive Mutation DE algorithm (SAMDE), which adopts an adaptive mutation operator that combines with the advantages of the DE/rand/1/bin strategy and the DE/best/2/bin strategy. As a result, its convergence performance is improved greatly. Numerical experiment results confirm the conclusion. The proposed SAMDE approach is effectively applied to test a numerical example and is compared with previous design methods. The computational experiments show that the SAMDE approach can obtain better results than previous design methods.

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“…In [11], the problem has been tackled using neural networks. In [12] and [13], a binary coded GA and a hybrid GA are attempted to solve this problem.…”

Section: Problem Formulationmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm

Wu¹,

Wang²,

Yuan³

2011

IJCIS

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Neural network‐based design of 2‐channel quadrature mirror filter banks

Jou

Lin

Chen

2018

Circuit Theory & Apps

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Two-channel quadrature mirror filter banks can be efficiently established by the combination of real-valued infinite impulse response all-pass filters without incurring aliasing and magnitude distortions. The design problem of filter banks is therefore to seek for the phase error minimization of the all-pass filter coefficients. In this paper, a neural network-based Lyapunov energy function is used to relate to the objective function of the designed all-pass filter coefficients. Based on the architecture of neural networks and suitable selection of Hopfield-related parameters, the all-pass filter coefficients are obtained when the networks reach convergence. By further using the suitable combination of the designed all-pass filters, the 2-channel quadrature mirror filter banks with perfect reconstruction can be efficiently accomplished. Simulation results indicate that the neural network-based approach has the advantage of satisfactory performance in magnitude and group delay responses in a parallelism manner.KEYWORDS all-pass filters, infinite impulse response, Lyapunov energy function, neural networks, quadrature mirror filter

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Design of Two-Dimensional IIR Filters Using an Improved DE Algorithm

Das

Dey

2005

Lecture Notes in Computer Science

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The paper investigates a novel technique of designing 2-dimensional IIR digital filters using a modified version of Differential Evolution (DE) where the scalar factor used for weighing the difference vector is made to vary randomly. This approach makes the classical DE more stochastic and provides it with additional exploration capability over the search space. The task of the design has been reformulated as a constrained minimization problem and is solved by the convergence of the proposed algorithm. Numerical example has been provided in support of the theoretical results. The paper also attempts to demonstrate the superiority of the proposed design method by comparing with a few previous design methods based on GA and neural networks.

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Design of two-dimensional recursive filters by using neural networks

Cited by 49 publications

References 18 publications

Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm

Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm

Neural network‐based design of 2‐channel quadrature mirror filter banks

Design of Two-Dimensional IIR Filters Using an Improved DE Algorithm

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