• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2005.11a
• /
• pp.250-255
• /
• 2005

In this paper, we propose a new fast running FIR filter structure that improves the convergence speed of adaptive signal processing and reduces the computational complexity. The proposed filter is applied to wavelet based adaptive algorithm. Actually we compared the performance of the proposed algorithm with other algorithm using computer simulation of adaptive noise canceler based on synthesis speech. As the result, the frequency domain algorithm is prefer than the existent time domain. we analyzed the Wavelet algorithm, short-length fast running FIR algorithm, fast-short-length fast running FIR algorithm and proposed algorithm.

• Journal of the Institute of Convergence Signal Processing
• /
• v.13 no.1
• /
• pp.19-25
• /
• 2012

An adaptive system is a well-known method for removing noise from noise-corrupted speech. In this paper, we perform a least mean square (LMS) based on wavelet adaptive algorithm. It establishes the faster convergence rate of as compared to time domain because of eigenvalue distribution width. And this paper provides the basic tool required for the FIR algorithm whose algorithm reduces the arithmetic complexity. We consider a new fast short-length running FIR structure in discrete wavelet adaptive algorithm. We compare FIR algorithm and short-length fast running FIR algorithm (SFIR) to the proposed fast short-length running FIR algorithm(FSFIR) for arithmetic complexities.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1991.06a
• /
• pp.38-41
• /
• 1991

RLS algorithms are required for applications to adaptive line enhancers, adaptive equalizers for voiceband telephone and HF modems, and wide-badn digital spectrum mobile raio in which their convergence time and tracking speed are significant. The fast QR RLS algorithm satisfies above the requirements. Its computational complexity is linearly proportional to the tap number of a filter, N and its performance remains numerically stable. From the result of simumulation, the fast QR RLS algorithm represented Cioffi is better than gradient based algorithm in its initial performance when being applied to an adaptive line enhancer for cancelling noise.

• Proceedings of the IEEK Conference
• /
• 2002.06d
• /
• pp.179-182
• /
• 2002

In this paper, we propose a wavelet based adaptive algorithm which improves the convergence speed and reduces computational complexity using the fast running FIR filtering efficiently We compared the performance of the proposed algorithm with time and frequence domain adaptive algorithm using computer simulation of adaptive noise canceler based on synthesis speech. As the result, the proposed algorithm is suitable for adaptive signal processing area using speech or acoustic field.

• Proceedings of the Korea Society of Information Technology Applications Conference
• /
• 2005.11a
• /
• pp.45-48
• /
• 2005

In this paper, we propose a new fast running FIR filter structure that improves the convergence speed of adaptive signal processing and reduces the computational complexity. The proposed filter is applied to wavelet based adaptive algorithm. Actually we compared the performance of the proposed algorithm with other algorithm using computer simulation of adaptive noise canceler based on synthesis speech. As the result, We know the proposed algorithm is prefer than the existent algorithm.

• Proceedings of the IEEK Conference
• /
• 2003.07e
• /
• pp.2459-2462
• /
• 2003

In this paper, we Propose a wavelet based adaptive algorithm which improves the convergence speed and reduces computational complexity using the fast running FIR filtering efficiently. We compared the performance of the proposed algorithm with time and frequence domain adaptive algorithm using computer simulation of adaptive noise canceler based on synthesis speech.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1379-1382
• /
• 1997

We introduce a fast implementation of the adaptive transversal filter which uses least-mean-square(LMS) algorithm. The fast Hadamard transform(FHT) is used for the implementation of the filter. By using the proposed filter we can get the significant time reduction in computatioin over the conventional time domain LMS filter at the cost of a little performance. By computer simulation, we show the comparison of the propsed Hadamard-domain filter and the time domain filter in the view of multiplication time, mean-square error and robustness for noise.

• The Journal of the Acoustical Society of Korea
• /
• v.17 no.2E
• /
• pp.3-9
• /
• 1998

Since the introduction of hands-free phone set and teleconferencing system, acoustic echo cancellation has been a challenge for engineers. Recently many researches have shown that the best solution for the acoustic echo compensation problem is represented by an adaptive filter which iteratively tries to identify the unknown impulse response of the system from loudspeaker to microphone. In this paper, we apply the delayless subband adaptive filters and fast affine projection algorithm for the identification of room impulse response. Simulation results show 3∼8 dB more enhanced performance than conventional fullband adaptive filters or subband adaptive filters. In addition, fast affine projection algorithm shows better convergence speed at the expense of the low computational complexity than conventional LMS algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.14 no.1
• /
• pp.27-32
• /
• 2003

This paper describes to extend the fast algorithm fur the capacitance extraction of large three-dimensional object. The triangular meshes are used and refined adaptively in the area where the heavy charges reside in each iterative solving. This technique is applied to the capacitance extraction of a 68-pin cerquad package. The results show fast convergence, and this adaptive technique coupled with the fast algorithm is efficient to reduce the number of elements and computing time with least additional computational efforts in large three dimensional problems.

• Journal of Korea Multimedia Society
• /
• v.8 no.8
• /
• pp.1051-1056
• /
• 2005

Least mean square(LMS) algorithm is one of the most popular algorithm in adaptive signal processing because of the simplicity and the small computation. But the convergence speed of time domain adaptive algorithm is slow when the spread width of eigen values is wide. Moreover we have to choose the step size well for convergency in this paper, we use adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm with variable step size, which Is linear to absolute value of error signal. We applied this algorithm to adaptive noise canceler. Simulation results are presented to compare the performance of the proposed algorithm with the usual algorithms.