FIR-filter design with spatial and frequency design constraints using evolution strategies

Franzen, O.; Blume, Holger; Schröder, Heiko

doi:10.1016/s0165-1684(98)00079-6

Cited by 11 publications

(3 citation statements)

References 7 publications

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“…In [23], they extended their work to complex cases to design arbitrary complex finite-duration impulse response (FIR) digital filters. Evolutionary strategies have also been applied to the design and optimization of FIR filters for video signal processing applications, as presented in [24]. Recently, a hybrid genetic algorithm was proposed by Cen in [25].…”

Section: Genetic Algorithmmentioning

confidence: 99%

Potential of Particle Swarm Optimization and Genetic Algorithms for FIR Filter Design

Boudjelaba

Ros

Chikouche

2014

Circuits Syst Signal Process

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Section: Genetic Algorithmmentioning

confidence: 99%

Potential of Particle Swarm Optimization and Genetic Algorithms for FIR Filter Design

Boudjelaba

Ros

Chikouche

2014

Circuits Syst Signal Process

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“…The standard Remez method [1], [7], for example, only considers the minimization of the maximum approximation error in the passbands and stopbands. Some techniques [3], [7], [8] have been proposed for the design of digital filters with constraints in the spatial and frequency domains. Recently, Franzen et al [3] proposed a design method based on the minimization of an overall error function using evolution strategies.…”

Section: Introductionmentioning

confidence: 99%

“…Some techniques [3], [7], [8] have been proposed for the design of digital filters with constraints in the spatial and frequency domains. Recently, Franzen et al [3] proposed a design method based on the minimization of an overall error function using evolution strategies. An important advantage of this method is that it allows us to directly influence desired filter properties in the spatial and frequency domains as well as the hardware expense.…”

Section: Introductionmentioning

confidence: 99%

Chebyshev Design of a Class Of FIR Filters With Frequency EquationConstraints

Lai

2002

Circuits, Systems, and Signal Processing

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This paper considers the design of finite impulse response (FIR) filters with equation constraints in the frequency domain and proposes a design algorithm. The design problem is formulated as Chebyshev approximation subject to equation constraints. The optimal filter is proved to have a characteristic property that there exists a set of frequencies including extremal frequencies where the weighted error takes a maximum value, and constraint frequencies where the response takes a given magnitude. According to this property, an orthogonal projection-based Remez exchange algorithm is proposed to solve the constrained Chebyshev design problem. As its application, the algorithm is applied to the design of FIR lowpass filters and notch filters. Simulation examples demonstrate the effectiveness and good performance of the proposed algorithm.

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Clutter and Noise Suppression Based on Match Filter

Chi

2017

Springer Proceedings in Physics

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FIR-filter design with spatial and frequency design constraints using evolution strategies

Cited by 11 publications

References 7 publications

Potential of Particle Swarm Optimization and Genetic Algorithms for FIR Filter Design

Potential of Particle Swarm Optimization and Genetic Algorithms for FIR Filter Design

Chebyshev Design of a Class Of FIR Filters With Frequency EquationConstraints

Clutter and Noise Suppression Based on Match Filter

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