• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12A
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• pp.2015-2024
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• 1999

Presented in this paper are a new complex-umber filter architecture, which is suitable for an efficient implementation of baseband signal processing of digital communication systems, and a chip-set design of adaptive decision-feedback equalizer (ADFE) employing the proposed structure. The basic concept behind the approach proposed in this paper is to apply redundant binary (RB) arithmetic instead of conventional 2’s complement arithmetic in order to achieve an efficient realization of complex-number multiplication and accumulation. With the proposed way, an N-tap complex-number filter can be realized using 2N RB multipliers and 2N-2 RB adders, and each filter tap has its critical delay of $T_{m.RB}+T_{a.RB}$ (where $T_{m.RB}, T_{a.RB}$are delays of a RB multiplier and a RB adder, respectively), making the filter structure simple, as well as resulting in enhanced speed by means of reduced arithmetic operations. To demonstrate the proposed idea, a prototype ADFE chip-set, FFEM (Feed-Forward Equalizer Module) and DFEM (Decision-Feedback Equalizer Module) that can be cascaded to implement longer filter taps, has been designed. Each module is composed of two complex-number filter taps with their LMS coefficient update circuits, and contains about 26,000 gates. The chip-set was modeled and verified using COSSAP and VHDL, and synthesized using 0.8- μm SOG (Sea-Of-Gate) cell library.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.1
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• pp.94-101
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• 2000

In this paper, a multi-channel active noise control(ANC) system using subband hybrid control techniques is proposed. Subband techniques could reduce computational burden and improve the performance of ANC systems by dividing several frequency subband and adjusting adaptive filter coefficients. So it can effectively cancel noises at wanted frequency range and use lower order adaptive filter than the existing algorithms. The adjoint LMS algorithm, which prefilter the error signals instead of the divided reference signals in frequency band, is also used for adaptive filter algorithms to reduce the computational burden of the subband adaptive systems. To improve performance of the ANC system, a weighted hybrid control technique, which has weightily properties of feedforward control systems and feedback control systems, is applied. This algorithm shows higher stability and good noise attenuation property in broad band ANC systems. Computer simulations were performed to show the effectiveness of the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.185-192
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• 2008

The crosstalk is the most serious problem in playing audio signals with more than two speakers. Usually an inverse filter is employed to remove such a Phenomenon. The LNS method, one of most effective design techniques for an inverse filter, has some advantages such as easy implementation and quick computation. However, the inverse filter designed by the LNS method is not easy to adapt immediately for the delivery system change since the pre-measured impulse response is used to design the filter. In this work, we present an adaptive algorithm for the inverse filter design. With the present algorithm. the inverse filter is initially designed by the LNS methods and continuously adjusted to cope with the delivery system changes. To verify the proposed method. some simulations were carried out and the results confirmed that the performance of the crosstalk calculation can be improved in entire frequency range.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.4 s.304
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• pp.45-50
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• 2005

In digital hearing aid system, one of the main problems is acoustic feedback which is known as howling because of miniaturization md high-gain amplification. In this paper, we proposed a feedback cancellation algorithm for hearing aid using time delay and time-varying decorrelation filter. The proposed algorithm has a kind of adaptive filter structure, which is combined with time delay and time-varying decorrelation filter to improve feedback cancellation. An all pass filter was implemented as the time-varying decorrelation filter using low frequency modulator. From the result of computer simulation, it is verified that the proposed algorithm has good ability to cancel feedback.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.101-106
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• 2015

In this paper, a shared band transmission, in which downlink signals from satellite to both earth station and user terminal are transmitted in the same frequency band, is considered. For proper operation of such shared band transmission, self-interference caused by the transmitted signal from its own transmitter should be cancelled and the desired signal from the other transmitter should be obtained. The self-interference is sent by its own transmitter and it can be easily regenerated with the estimated round-trip delay. In addition to this delay, non-linearity effects caused by power amplifiers at the earth station and satellite should be exploited. The proposed interference canceller divided into two parts: one is subtraction of the transmitted signal with delay and non-linearity effects, and the other is adoptive filter to suppressed the residual interference. Through computer simulations, the effectiveness of the proposed system is verified.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1249-1256
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• 2019

In this paper, we propose a new algorithm to remove acoustic feedback and noise in hearing aids. Instead of using the conventional FIR structure, this algorithm is a deep learning algorithm using neural network adaptive prediction filter to improve the feedback and noise reduction performance. The feedback canceller first removes the feedback signal from the microphone signal and then removes the noise using the Wiener filter technique. Noise elimination is to estimate the speech from the speech signal containing noise using the linear prediction model according to the periodicity of the speech signal. In order to ensure stable convergence of two adaptive systems in a loop, coefficient updates of the feedback canceller and noise canceller are separated and converged using the residual error signal generated after the cancellation. In order to verify the performance of the feedback and noise canceller proposed in this study, a simulation program was written and simulated. Experimental results show that the proposed deep learning algorithm improves the signal to feedback ratio(: SFR) of about 10 dB in the feedback canceller and the signal to noise ratio enhancement(: SNRE) of about 3 dB in the noise canceller than the conventional FIR structure.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.38-46
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• 2012

Atrial fibrillation is needed to be detected at paroxysmal stage and to be treated. But, paroxysmal atrial fibrillation ECG is hardly obtained with 12-lead electrocardiographs but Holter systems. Presently, the averaged beat subtraction(ABS) method is solely used to estimate atrial fibrillatory waves even with somewhat large residual error. As an alternative, in this study, we suggested an ESAF(event-synchronous adaptive filter) based algorithm, in which the AF ECG was treated as a primary input and event-synchronous impulse train(ESIT) as a reference. And, ESIT was generated so to be synchronized with the ventricular activity by detecting QRS complex. We tested proposed algorithm with simulated AF ECGs and real AF ECGs. As results, even with low computational cost, this ESAF based algorithm showed better performance than the ABS method and comparable performance to algorithm based on PCA(principal component analysis) or SVD(singular value decomposition). We also proposed an expanded version of ESAF for some AF ECGs with multi-morphologic ventricular activities and this also showed reasonable performance. Ultimately, with Holter systems including our proposed algorithm, atrial activity signal can be precisely estimated in real-time so that it will be possible to calculate atrial fibrillatory rate and to evaluate the effect of anti-arrhythmic drugs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.447-454
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• 2011

Power-line interference(PLI) can distort certain regions in analysing the ECG signal. In particular, the regions such as P and R wave that are important element in diagnosing with arrhythmia is expressed as different type of noise according to the case whether power-line frequency is multiples of sampling frequency and or not. Noise characteristics is also divided into linearity and non-linearity. In this paper, adaptive subtraction method for removing variable PLI of ECG signal is proposed. We classify the multiple relationship between power line and sampling frequency as Multiple and Non-multiple. PLI of Linear segment is extracted through moving average filter, PLI of non-linear segment is extracted through the interference component that is extracted in the linear segment and stored in the temporary buffer. The performance of P wave and R wave detection is evaluated by using 119 data record of MIT-BIH arrhythmia database. The achieved scores indicate P wave detection rate of 97.91%, R wave detection rate of 96.66% and P wave detection rate of 99.01%, R wave detection rate of 97.93% accuracy respectively for Notch filter and proposed subtraction method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.81-87
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• 2016

This paper analysis the AM-SCS-MMA (Adaptive Modulus-Soft Constraint Satisfaction-MMA) based on the adaptive modulus and minimus-disturbance technique in order to improve the stability and robustness in low signal to noise power of current MMA adaptive equalization algorithm. In AM-SCS-MMA, it updates the filter coefficient applying the adaptive modulus and minimum-disturbance technique of deterministic optimization problem instead of LMS or gradient descend algorithm for obtain the minimize the cost function of adaptive equalization. It is possible to improve the equalizer filter stability, robustness to the various noise characteristic and simultaneous reducing the intersymbol interference due to the amplitude and phase distortion occurred at channel. The computer simulation were performed for confirming the improved performance of SCS-MMA. For these, the output signal constellation of equalizer, residual isi, MSE, EMSE (Excess MSE) which means the channel traking capability and SER which means the robustness were applied. As a result of computer simulation, the AM-SCS-MMA have slow convergence time and less residual quantities after steady state, more good robustness in the poor signal to noise ratio, but poor in channel tracking capabilities was confirmed than MMA.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.49-59
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• 2009

In this paper a watermarking algorithm is proposed to optimize the capacity of the digital watermark insertion in an experimental threshold using the characteristics of human visual system(HVS), adaptive scale factors, and weight functions based on discrete wavelet transform. After the original image is decomposed by a 3-level discrete wavelet transform, the watermarks for capacity optimization are inserted into all subbands except the baseband, by applying the important coefficients from the experimental threshold in the wavelet region. The adaptive scale factors and weight functions based on HVS are considered for the capacity optimization of the digital watermark insertion in order to enhance the robustness and invisibility. The watermarks are consisted of gaussian random sequences and detected by correlation. The experimental results showed that this algorithm can preserve a fine image quality against various attacks such as the JPEG lossy compression, noise addition, cropping, blurring, sharpening, linear and non-linear filtering, etc.