• The Journal of the Acoustical Society of Korea
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• v.27 no.3E
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• pp.95-103
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• 2008

In this paper, the new hybrid adaptive Volterra filter was proposed to be applied for compensating the nonlinear distortion of memoryless nonlinear systems with saturation characteristics. Through computer simulations as well as the analytical analysis, it could be shown that it is possible for both conventional Volterra filter and proposed hybrid Volterra filter, to be applied for linearizing the memoryless nonlinear system with nonlinear distortion. Also, the simulations results demonstrated that the proposed hybrid filter may have faster convergence speed and better capability of compensating the nonlinear distortion than the conventional Volterra filter.

• The Journal of the Acoustical Society of Korea
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• v.18 no.2
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• pp.61-65
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• 1999

This paper derives a sufficient condition on the stability of recursive third-order Volterra filters based on their filter coefficients. A Volterra filter is very effective in modeling nonlinear systems with memory. However, it is well-known that the nonrecursive Volterra filter requires a large number of filter coefficients to describe a nonlinear system. For this reason, recursive Volterra filters are usually considered because the recursive implementation requires a smaller number of coefficients compared to the nonrecursive one. Unfortunately, the main problem of the recursive Volterra filters is their inherent instablility. In this paper. we present a simple condition for the output of a recursive discrete-time third-order Volterra filter to be bounded whenever the input signal to the recursive Volterra filter is bounded by a finite constant.

• Journal of IKEEE
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• v.17 no.2
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• pp.111-118
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• 2013

In this paper, the subband nonlinear adaptive Volterra filters are introduced and its analysis are presented. From the eigenvalue analysis of the input correlation matrix, we show that the proposed subband adaptive Volterra filter has superior convergence performance as compared to the conventional one, which shows that the it can be useful for the recently proposed subband nonlinear adaptive echo canceller. Also, the optimum filter in each subband are introduced and verified from the computer simulations.

• The Journal of the Acoustical Society of Korea
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• v.12 no.1
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• pp.37-46
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• 1993

The adaptive algorithm for the Volterra filter is considered. Owing to its simplicity, the LMS algorithm for adaptive Volterra filter(AVF) is widely used as in linear adaptive filters. However, the convergence speed is unsatisfactory. For improving the convergence speed, the frequency domain LMS second order adaptive Volterra filter(FLMS-AVF) is proposed and analyzed. We show that the time and frequency domain LMS AVF's have the same steady state performance under approprate conditons. Moreover, it can be shown that this algorithm can improve the convergence speed significantly by applying self-orthogonalizing method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.59-65
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• 2012

In this paper, we investigate the compressed sensing (CS) algorithms for modeling a super-resolution near-field structure (super-RENS) disc system with a sparse Volterra filter. It is well known that the super-RENS disc system has severe nonlinear inter-symbol interference (ISI). A nonlinear system with memory can be well described with the Volterra series. Furthermore, CS can restore sparse or compressed signals from measurements. For these reasons, we employ the CS algorithms to estimate a sparse super-RENS read-out channel. The evaluation results show that the CS algorithms can efficiently construct a sparse Volterra model for the super-RENS read-out channel.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.205-209
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• 2013

A conventional acoustic echo suppressor (AES) considering only room impulse response between a loudspeaker and a microphone eliminates acoustic echo from the microphone input. However, in a nonlinear acoustic echo environment, the conventional AES degraded because of a nonlinearity of the loudspeaker. In this paper, we adopt AES based on the frequency-domain second-order Volterra filter using Least Square method. For comparing performances, we conduct objective tests including Echo Return Loss Enhancement (ERLE) and Speech Attenuation (SA). The proposed algorithm shows better performance than the conventional in both linear and nonlinear acoustic echo environments.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.16-19
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• 1996

The objective of this paper is to present a new adaptive nonlinear compensation method, which is based upon the Pth-order inverse theory and can be implemented in a systematic way, for weakly nonlinear systems that can be modeled by a Volterra series. In particular, employment of the proposed approach for the linearization of a given nonlinear system leads to the effective elimination of (up to a required order) nonlinearities in the overall system output. To demonstrate the feasibility of the proposed method, simulation results using a satellite communication system model are also provided.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.981-982
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• 2008

In this paper, Kalman-LMS algorithm is further extended to nonlinear system identification, whereby Kalman-LMSalgorithm and third-order Volterra filer are utilized.

• Journal of IKEEE
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• v.24 no.2
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• pp.570-578
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• 2020

In this paper, we propose an efficient method for implementing the adaptive second-order Volterra filter. To reduce computational load, the UCFD-SVF has been proposed. The UCFD-SVF, however, shows deteriorated convergence performance. We propose a new method that initializes the adaptive filter weights periodically on the fact that the energy of the filter weights is slowly increased. Furthermore, we propose another method that the interval for the weight initialization is variable to guarantee the performance and we shows the method gives the better performance under the non-stationary environment through the computer simulation for the adaptive system identification.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.23-33
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• 1996

In this paper we point out that if the classical principal domain for bispectra is utilized to determine a second-order Volterra model's output, such and output will be incomplete. This deficiency is associated with the periodic nature of the DFT. For this reason, the objective of this paper is to present an "extended" principal domain for Volterra kernels which leads to an improved estimate of the nonlinear system's response. In order to define the extended principal domain, we derive a new discrete frequency-domain Volterra model from a discrete time-domain Volterra model utilizing 2-dimensional DFT and the relationship between the quadratic component of the Volterra model and a square filter. The effect of the extended domain on the model output is interpreted in terms of the periodicity of DFT. Through computer simulations, we demonstrate the effects of the extended principal domain on the Volterra modeling. The simulation results indicate that the extended principal domain plays and important role in computing Volterra model outputs and estimating Volterra model coefficients.