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

• 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.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.191-194
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• 2000

Frequency domain adaptive filter is effective to communication fields of many computational requirements. In this paper we propose a new variable step size algorithms which improves the convergence speed and reduces computational complexity for frequency domain adaptive filter. we compared MSE of the proposed algorithms with one of normalized FLMS using computer simulation of adaptive noise canceler based on synthesis speech.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1234-1238
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• 2005

As the low power GPS signal is susceptible to interference, interference can seriously degrade the performance of GPS receiver. This paper designs a ANIEF(Adaptive Narrowband Interference Excision in Frequency domain) filter that removes narrow band interferences with low signal loss. This filter uses the pre-correlation technique and attempts to filter out the interference in the frequency domain. The interference excision performance of the designed filter is evaluated for various interferences using the ANIEF filter inserted GPS software receiver and the interference generator. Interferences considered in this paper are single-tone CWI(Continuous Wave Interference), multi-tones CWI, pulsed CWI, and swept CWI. The narrowband interference excision filter in frequency domain is very effective against various interferences and the strong interference with a simple structure. However, the signal power loss is unavoidable while transforming. In this paper, the hamming window and overlap technique are adopted to reduce the signal power loss. Finally, the interference excision performance and the reduced signal power loss of the ANIEF filter are shown.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.6
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• pp.308-316
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• 1985

A new implementation of Block Adaptive filter in frequency domain is presented in this paper. Block digital filtering involves the calculation of a block or finite set of filter out put from a block of input values. A fast convergence algorithm of block adaptive filter is developed using Gordar theory and compared with the performance results of Satio algorithm and BLMS algorithm. Form the result we can be shown that the convergence state of given algorithm is not only faster than BLMS algorithm but also the resulting convergence error is less than the convergence error of Satio algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.240-240
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• 2000

This paper presents two algorithms based on the concept of the frequency domain adaptive filter(FDAF). First the frequency domain recursive least squares(FRLS) algorithm with the overlap-save filtering technique is introduced. This minimizes the sum of exponentially weighted square errors in the frequency domain. To eliminate discrepancies between the linear convolution and the circular convolution, the overlap-save method is utilized. Second, the sliding method of data blocks is studied Co overcome processing delays and complexity roads of the FRLS algorithm. The size of the extended data block is twice as long as the filter tap length. It is possible to slide the data block variously by the adjustable hopping index. By selecting the hopping index appropriately, we can take a trade-off between the convergence rate and the computational complexity. When the input signal is highly correlated and the length of the target FIR filter is huge, the FRLS algorithm based on the block processing technique has good performances in the convergence rate and the computational complexity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.673-677
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• 2003

In this study, we propose the new filter bank that is adaptive filter bank using neural networks in time domain. Also, we proposed a new filter neuron as neuron with filter window, the structure and algorithm for filter banks. The performance of neural filter banks is shown from two examples. It show characteristics the simple structure and higher speed processing than traditional methods (filter banks in frequency domain, etc.). In many applications, the proposed method will provide the high performance to features detection of signals in time domain.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.231-238
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• 2004

This paper presents the high speed noise reduction processing system using the modified discrete fourier transform(MDFT) on the frequency domain. The proposed filter uses the linear prediction coefficients of the adaptive line enhance(ALE) method based on the Sign algorithm The signals with a random noise tracking performance are examined through computer simulations. It is confirmed that the fast adaptive digital filter is realized by the high speed adaptive noise reduction(HANR) algorithm with rapid convergence on the frequency domain(FD).

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.225-228
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• 2000

It is well known that a Frequency Domain Adaptive Filter (FDAF) converges faster than a Time Domain Adaptive Filter (TDAF) even when the input signal is colored such as a speech signal. We have proposed the FDAF using the Modified Discrete Fourier Transform Pair (MDFTP) and its realization and effectiveness has been confirmed through the computer simulations. In this paper, we apply the FDAF using the MDFTP to the noise cancellation system. The proposed system is based on the Adaptive Line Enhancer (ALE) and utilizes single microphone; therefore it is suitable for the portable electronic equipment. Moreover, we propose to utilize the MDFT for detecting of the pitch in the speech because the number of data points in the MDFT must be equal to the pitch to confirmed that the noise can be removed to near the level of SNR.

• The Journal of the Acoustical Society of Korea
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• v.35 no.4
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• pp.272-279
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• 2016

In this paper, the realization of a hearing aid adaptively cancelling feedback noise was considered. Conventional least mean square method in time domain was transformed into frequency domain in order to minimize computational burden. The adaptive filter algorithm was evaluated by Matlab (Matrix laboratory), and it was confirmed by CSR 8675 Bluetooth DSP IC (Digital Signal Processor Integrated Circuit) chip firmware realization. Some remote control features by a smart phone was added to the smart hearing aid for user interface easiness.