• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.696-705
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• 1997

This paper presents an efficient adaptive predistortion technique compensating linear and nonlinear distortions caused by high-power amplifier (HPA) with memory in OFDM systems. The efficient adaptive data predistortion techniques proposed for compensation of HPA with memory in single carrier systems cannot be applied to OFDM systems since the possible input levels for HPA is infinite in OFDM systems. Also, previous adaptive predistortion techniques, based on Volterra series modeling, are not suitable for real-time implementation due to high computational burden and slow convergence rate. In the proposed approach, the memoryless HPA preceded by a linear filter in OFDM systems is modeled by the Wiener system which is then precompensated by the proposed adaptive predistorter with a minimum number of filter taps. An adaptive algorithm for adjusting the proposed adaptive predistorter is derived using the stochastic gradient method. It is demonstrated by computer simulation that the performance of OFDM system suffering from nonlinear distortion can be greatly improved by the proposed efficient adaptive predistorter using a small number of filter taps.

• Journal of Mechanical Science and Technology
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• v.16 no.3
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• pp.310-319
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• 2002

This paper deals with the analytical modeling, and the experimental verification of the strain rate self-sensing method using a hybrid adaptive filter for a cantilevered piezoelectric beam. The piezoelectric beam consists of two laminated lead zirconium titanates (PZT) on a metal shim. A mathematical model of the beam dynamics is derived by Hamilton's principle and the accuracy of the modeling is verified through the comparison with experimental results. For the strain rate estimation of the cantilevered piezoelectric beam, a self-sensing mechanism using a hybrid adaptive filter is considered. The discrete parts of this mechanism are realized by the DS1103 DSP board manufactured by dSPACE$\^$TM/. The efficacy of this method is investigated through the comparison of experimental results with the predictions from the derived analytical model.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.295-303
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• 2008

In general, transform domain adaptive filters show faster convergence speed than the time domain adaptive filters, but the amount of calculation increases dramatically as the filter order increases. This problem can be solved by making use of the subband structure in transform domain adaptive filters. In this paper, to increase the convergence speed on the generalized subband decomposition FIR adaptive filters, a structure of the adaptive filter with subfilter of dyadic sparsity factor in wavelet transform domain is designed. And, in this adaptive filter, the equivalent input in transform domain is derived and, by using the input, the convergence properties for the LMS algorithm is analyzed and evaluated. By using this sub band adaptive filter, the inverse system modeling and the periodic noise canceller were designed, and, by computer simulation, the convergence speeds of the systems on LMS algorithm were compared with that of the subband adaptive filter using DFT(discrete Fourier transform).

• The Journal of the Acoustical Society of Korea
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• v.22 no.1E
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• pp.33-42
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• 2003

Kuo et al proposed an on-line method for an adaptive prediction error filter for improving secondary path modeling performance in the modeling method of the secondary path. This method have some disadvantages, namely having to use additive noise with the result that noise control performance is not good since it is focused on the estimated performance of the secondary path. In this paper, we proposes a modified Kuo model using gain control parameter and delay. It uses a reference signal for additive noise to improve the problems in the existing Kuo model.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.165-170
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• 1995

In this paper, it is attempted to apply the adaptive digital signal processing to compensate for a linear distortion of a loudspeaker and implement a real time hardware for that purpose. The real time system is implemented by using the DSP56001, a general purpose signal processor, as a host processor and the DSP56200, a cascadable adaptive FIR filter peripheral chip, as an adaptive digital filter. The system has 1000 taps at a 44.1kHz. After inverse modeling of under_compensation_speaker, the system reduces loudspeaker's linear distortions by pre-processing an input audio signal to loudspeaker. The experiment shows satisfactory results; after adaption with white noise as input signal for 60sec, the flat amplitude and linear phase frequency characteristics is found to lie over a wide frequency range of 100Hz to 20kHz.

• The Journal of the Acoustical Society of Korea
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• v.16 no.3E
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• pp.44-49
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• 1997

In this paper, we propose an adaptive encoding method of fixed codebook in CELP coders and implement an adaptive fixed code exited linear prediction(AF-CELP) speech coder. AF-CELP exploits the fact that the fixed codebook contribution to speech signal is also periodic like the adaptive codebook (or pitch filter) contribution. By modeling the fixed code book with the pitch lag and the gain from the adaptive codebook, AF-CELP can be implemented at low bit rates as well as low complexity. Listening tests show that a 6.4 kbit/s AF-CELP has a comparable quality to the 8 kbit/s CS-ACELP in background noise conditions.

• ETRI Journal
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• v.38 no.6
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• pp.1190-1196
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• 2016

We propose a new bandpass filter (BPF)-based online channel normalization method to dynamically suppress channel distortion when the speech and channel noise components are unknown. In this method, an adaptive modulation frequency filter is used to perform channel normalization, whereas conventional modulation filtering methods apply the same filter form to each utterance. In this paper, we only normalize the two mel frequency cepstral coefficients (C0 and C1) with large dynamic ranges; the computational complexity is thus decreased, and channel normalization accuracy is improved. Additionally, to update the filter weights dynamically, we normalize the learning rates using the dimensional power of each frame. Our speech recognition experiments using the proposed BPF-based blind channel normalization method show that this approach effectively removes channel distortion and results in only a minor decline in accuracy when online channel normalization processing is used instead of batch processing

• The Journal of the Acoustical Society of Korea
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• v.17 no.1E
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• pp.36-43
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• 1998

A fuzzy logic filter is constructed from a set of fuzzy IF-THEN rules which change adaptively to minimize some criterion function as new information becomes available. This paper generalizes the fuzzy logic filter and it's adaptive filtering algorithm to include complex parameters and complex signals. Using the complex Stone-Weierstrass theorem, we prove that linear combinations of the fuzzy basis functions are capable of uniformly approximating and complex continuous function on a compact set to arbitrary accuracy. Based on the fuzzy basis function representations, a complex orthogonal least-squares (COLS) learning algorithm is developed for designing fuzzy systems based on given input-output pairs. Also, we propose an adaptive algorithm based on LMS which adjust simultaneously filter parameters and the parameter of the membership function which characterize the fuzzy concepts in the IF-THEN rules. The modeling of a nonlinear communications channel based on a complex fuzzy is used to demonstrate the effectiveness of these algorithm.

• The Journal of the Acoustical Society of Korea
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• v.34 no.3
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• pp.177-183
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• 2015

This paper proposes a robust nonlinear acoustic echo canceller (NAEC) which is effective for modeling the nonlinearity of a speaker module and the long acoustic echo path within a speech communication environment. The proposed NAEC utilizes a sigmoid pre-processor for modeling the speaker nonlinearity and a partitioned block frequnecy-domain adaptive filter for identifying the acoustic echo path with small delay. Simulation results confirmed that the proposed algorithm achieves excellent performance with much lower computational complexity than the previous NAEC.

• Journal of KSNVE
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• v.2 no.2
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• pp.107-116
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• 1992

An adaptive signal processing technique is implemented for the active noise cancellation of the plane acoustic wave propagating in a duct. To avoid the instability caused by the acoustic feedback from the control speaker to the detect microphone, an off-line modeling of the acoustic feedback plant is done using the FIR filter. Auxiliary path required for the filtered-x LMS algorithm is modeled as well. Before going into the experiments, a simulation is carried out under the same conditions with experiments. The simulation shows that the longer the length of the adaptive filter is, the better the results are achieved. Experiments have been carried out at lower audio frequency range (50 - 400Hz), and the results are in good agreements with those of simulation study. As a results of this adaptive noise control, around 50dB is reduced for a pure tone noise, and for a bandlimited noise with the bandwidth of 316Hz, a maximum of 30dB noise reduction is attained.