• Speech Sciences
• /
• v.11 no.2
• /
• pp.227-235
• /
• 2004

In this paper, we proposed a new practical implementation method of the lattice transversal joint (LTJ) adaptive filter using speech codec's information. And it was applied to the adaptive echo cancellation problem to verify the efficiency of the proposed method. Realtime implementation of the LTJ adaptive filter is very difficult due to high computational complexity for the filter coefficients compensation. However, in case of using speech codec, complexity can be reduced since linear predictive coding (LPC) coefficients are updated each frame or sub-frame instead of every sample. Furthermore, LPC coefficients can be acquired from speech decoder and transformed to the reflection coefficients. Therefore, the computational complexity for updates of the reflection coefficients can be reduced. The effectiveness of the proposed LTJ adaptive filter was verified by the experiments about convergence and tracking performance of the adaptive echo canceller.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2003.05b
• /
• pp.427-430
• /
• 2003

This paper proposes a modified generalized side-lobe canceller with a summed adaptive filter and an adaptive compensator. A summed adaptive filter reduces computational loads and the adaptive compensator minimizes the misadjustment of the adaptive filter coefficients . Computer simulations explain the performance improvement of the proposed method and the conventional generalized side-lobe canceller.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.7
• /
• pp.688-693
• /
• 2007

The INS/GPS integration system is designed by employing an adaptive filter that can estimate the measurement noise variance using the residual of the filter. To verify the efficiency of the proposed loosely-coupled INS/GPS integration system, simulation is performed by assuming that GPS information has large position errors. Simulation results show that the proposed integration system with the adaptive filter is more effective in estimating the position and attitude errors than those with the Extended Kalman Filter.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.22 no.2
• /
• pp.18-24
• /
• 1985

Above certain filter order, the frequency domain -adaptive filter is superior to the time domain-adaptive filter in computational complexity. In this paper a new type algorithm, $\mu$-FLMs algorithm, is proposed for the frequency domain- adaptive filter and the characteristics of the proposed algorithm is compared with that of the time domain- adaptive filter algorithm($\mu$-FLMS algorithm). The simulation results showed that under the same convergence rate , the frequency domain-adaptive filter is efficient in compu tational burden.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.81-84
• /
• 2001

We propose a novel noise littering method based on adaptive windowing. To restore a noisy signal adaptive filtering methods have been widely researched and used. However, conventional adaptive filtering methods have a trade-off between noise suppression and edge preservation since they adopt fixed size filters. In this paper applying the adaptive windowing concept to adaptive filtering, we overcome the trade-off, The filter size is adaptively selected depending on signal statistics. The visual results of the signal and image restorations convincingly show the superior preservation of edge and detail and suppression of noise for the proposed adaptive windowed adaptive filter compared with conventional methods.

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.377-380
• /
• 2002

When it calculates the optimum price of filter coefficient, the many operation quantity is necessary. Is like that the real-time control is difficult and the hardware embodiment expense is big. The case which does not know advance information of input signal or the case where the statistical nature changes with change of surroundings environment is necessary the adaptive filter. Every hour to change a coefficient automatically and system in order to reach to the condition of optimum oneself, the fact that is the adaptive filter. When it does not the quality of input signal or it does not know the environment of surroundings every hour changing, it does not emit not to be, in order to collect, the fact that is the adaptive filter. The case of the Acoustic Echo Canceler does thousands filter coefficients in necessity. It reduces a many calculation quantity to respect, it uses the IIR filter from hour territory. Also it uses the block adaptive filter which has a block input signal and a block output signal. The former there is a weak point where the stability discrimination is always demanded. Consequently, The block adaptive filter is researched plentifully. This dissertation planned the block MADF adaptive filter used to MADf algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.11 no.5
• /
• pp.59-63
• /
• 2011

We present a lattice transversal joint (LTJ) adaptive filter with fixed reflection coefficients to achieve fast convergence with low complexity. The reflection coefficients of the filter are given by the statistics of speech signals, and the proposed order of the lattice predictor is one. Experimental results confirm that as compared to the adaptive transversal filter, the proposed adaptive filter achieves fast convergence with a negligible increase in complexity. The proposed adaptive filter converges around six times faster than the adaptive transversal filter in case of the band-limited voiced signal from the ITU-T G.168 standard.

• The Journal of the Acoustical Society of Korea
• /
• v.33 no.5
• /
• pp.335-340
• /
• 2014

In this paper, we propose a new sign subband adaptive filter to improve the convergence rate of the conventional sign subband adaptive filter which has been proposed to deal with colored input signal under the environment with impulsive noise. The existing sign subband adaptive filter does not increase the convergence speed by increasing the number of subband because each subband input signal is normalized by $l_2-norm$ of all of the subband input signals. We devised a new sign subband adaptive filter that normalizes each subband input signal with $l_2-norm$ of each subband input signal and increases the convergence rate by increasing the number of subband. We carried out a performance comparison of the proposed algorithm with the existing sign subband adaptive filter using a system identification model. It is shown that the proposed algorithm has faster convergence rate than the existing sign subband adaptive filter.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.10
• /
• pp.2339-2347
• /
• 1997

The performance of the adaptive noise canceller using LMS algorithm is degraded by the gradient noise due to target speech signals. An adaptive noise canceller with speech detector was proposed to reduce this performande degradation. The speech detector utilized the adaptive prediction-error filter adapted by the NLMS algorithm. This paper discusses to enhance the performance of the adaptive noise canceller forthecorlored noise. The affine projection algorithm, which is known as faster than NLMS algorithm for correlated signals, is used to adapt the adaptive filter and the adaptive prediction error filter. When the voice signals are detected by the speech detector, coefficients of adaptive filter are adapted by the sign-error afine projection algorithm which is modified to reduce the miaslignment of adaptive filter coefficients. Otherwirse, they are adapted by affine projection algorithm. To obtain better performance, the proper step size of sign-error affine projection algorithm is discussed. As resutls of computer simulation, it is shown that the performance of the proposed ANC is better than that of conventional one.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.1
• /
• pp.31-36
• /
• 2009

This paper presents a novel scalar adaptive filter, which is reformulated by additional acceleration term. The filter continuously estimates three different kinds of covariance such as the measurement noise covariance, the velocity error covariance and the acceleration error covariance. For estimating three covariances, we use the innovation method for the measurement noise covariance and the least square method for other covariances. In order to verify the proposed filter performance compared with the conventional scalar adaptive filter, we make indoor experimental environment similar to outdoor test using the ultrasonic sensors instead of GPS. Experimental results show that the proposed filter has better position accuracy than the traditional scalar adaptive filter.