• 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 KIEE Conference
• /
• 2003.04a
• /
• pp.212-216
• /
• 2003

The performance of active power filter depends on the inverter characteristic, the control method, and the accuracy of reference signal generator. The accuracy of reference generator is the most critical item to determine the performance of active power filter. This paper introduces a novel reference signal generator composed of improved adaptive predictive filter. The performance of proposed reference signal generator was verified by means of simulation with MATLAB. The simulation result confirm that the proposed reference signal generator can be utilized for the active power filter.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.9 no.6
• /
• pp.592-601
• /
• 2004

The performance of active power filter depends on the inverter characteristic, the control method, and the accuracy of reference signal generator. The accuracy of reference signal generator is the most critical item to determine the performance of active power filter. This paper introduces a novel reference signal generator composed of improved adaptive predictive filter. The performance of proposed reference signal generator was verified by means of simulation with MATLAB. The application feasibility was evaluated by building and experimenting a single-phase active power filter based on the proposed reference generator, which was implemented in the DSP(digital signal processor) TMS320C31. Both simulation and experimental results confirm that the proposed reference signal generator can be utilized for the active power filter.

• Journal of the military operations research society of Korea
• /
• v.13 no.1
• /
• pp.1-18
• /
• 1987

This paper presents several adaptive linear predictive coding techniques based upon extension of recursive ladder filters. A 2-D recursive ladder filter is extended to a 3-D case which can adaptively track the variation of both spatial and temporal changes of moving images. Using the 2-D/3-D ladder filter and a previous farme predictor, two types of adaptive predictor-control schemes are proposed in which the prediction error at each pel can be obtained at or close to a minimum level. We also investigate several modifications of the basic encoding methods. Performance of the 2-D/3-D ladder filters, their adaptive control schemes, and variations in coding methods are evaluated by computer simulations on a real sequence and compared to the results of motion compensation and frame differential coders. As a validity test of the ladder filters developed, the error signals for the different predictors are compared and evaluated.

• Proceedings of the KIPE Conference
• /
• 2005.07a
• /
• pp.494-497
• /
• 2005

In this paper, harmonic detecting methods for the active power application are investigated. They are RDFT, Kalman Filter, Adaptive predictive filter, Instantaneous reactive power detecting method, Improved adaptive filter detecting method. The 5 harmonic detecting methods are simulated and their characteristics for the active filter application are compared using simulation results.

• Journal of Power Electronics
• /
• v.11 no.5
• /
• pp.751-758
• /
• 2011

This paper presents an effective robust predictive control scheme for the active power filter (APF) using a smith-predictor based current regulator, which show superior features when compared to proportional-integral (PI) controllers in terms of an enhanced closed-loop bandwidth and an improved current tracking accuracy. A moving average filter (MAF) is implemented using a field programmable gate array (FPGA) for signal pre-processing to eliminate the switching ripple contamination. An adaptive linear neural network (ADALINE) is used for individual harmonic estimation to achieve selective compensation purpose. The effectiveness and validity of the devised control algorithm are confirmed by extensive simulation and experimental results.

• Structural Engineering and Mechanics
• /
• v.83 no.4
• /
• pp.537-549
• /
• 2022

In this paper, a novel multi-feature model predictive control (MPC) framework with real-time and adaptive performances is proposed for intelligent structural control in which some drawbacks of the algorithm including, complex control rule and non-optimality, are alleviated. Hence, Linear Programming (LP) is utilized to simplify the resulted control rule. Afterward, the Whale Optimization Algorithm (WOA) is applied to the optimal and adaptive tuning of the LP weights independently at each time step. The stochastic control rule is also achieved using Kalman Filter (KF) to handle noisy measurements. The Extreme Learning Machine (ELM) is then adopted to develop a data-driven and real-time control algorithm. The efficiency of the developed algorithm is then demonstrated by numerical simulation of a twenty-story high-rise benchmark building subjected to earthquake excitations. The competency of the proposed method is proven from the aspects of optimality, stochasticity, and adaptivity compared to the KF-based MPC (KMPC) and constrained MPC (CMPC) algorithms in vibration suppression of building structures. The average value for performance indices in the near-field and far-field (El earthquakes demonstrates a reduction up to 38.3% and 32.5% compared with KMPC and CMPC, respectively.

• Journal of Power Electronics
• /
• v.17 no.6
• /
• pp.1587-1599
• /
• 2017

This paper proposes a real-time implementation of an optimal operation of a double stage grid connected wind power system incorporating an active power filter (APF). The system is used to supply the nonlinear loads with harmonics and reactive power compensation. On the generator side, a new adaptive neuro fuzzy inference system (ANFIS) based maximum power point tracking (MPPT) control is proposed to track the maximum wind power point regardless of wind speed fluctuations. Whereas on the grid side, a modified predictive current control (PCC) algorithm is used to control the APF, and allow to ensure both compensating harmonic currents and injecting the generated power into the grid. Also a type 2 fuzzy logic controller is used to control the DC-link capacitor in order to improve the dynamic response of the APF, and to ensure a well-smoothed DC-Link capacitor voltage. The gained benefits from these proposed control algorithms are the main contribution in this work. The proposed control scheme is implemented on a small-scale wind energy conversion system (WECS) controlled by a dSPACE 1104 card. Experimental results show that the proposed T2FLC maintains the DC-Link capacitor voltage within the limit for injecting the power into the grid. In addition, the PCC of the APF guarantees a flexible settlement of real power exchanges from the WECS to the grid with a high power factor operation.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.51 no.2
• /
• pp.69-77
• /
• 2002

Speaker verification can be classified in two categories, text-dependent speaker verification and text-independent speaker verification. In this paper, we discuss text-dependent speaker verification. Text-dependent speaker verification system determines whether the sound characteristics of the speaker are equal to those of the specific person or not. In this paper we obtain the speaker data using a sound card in various noisy conditions, apply a new Hidden LMS (Least Mean Square) adaptive algorithm to it, and extract LPC (Linear Predictive Coding)-cepstrum coefficients as feature vectors. Finally, we use a competitive learning neural network for speaker verification. The proposed hidden LMS adaptive filter using a neural network reduces noise and enhances features in various noisy conditions. We construct a separate neural network for each speaker, which makes it unnecessary to train the whole network for a new added speaker and makes the system expansion easy. We experimentally prove that the proposed method improves the speaker verification performance.

• Proceedings of the KIEE Conference
• /
• 1987.07b
• /
• pp.1422-1426
• /
• 1987

In this paper, an adaptive DPCM scheme is presented for encoding monochrome images with easy hardware implementation at a transmission rate of exactly 1 bit/pel. The system is mainly composed of a compensated mean predictor and an adaptive two-level quantizer with backward estimation. In this system, the predictor is a sort of two-dimensional ARMA predictor in which a moving-average part is added to the conventional mean predictor. The quantizer adapts to the local statistics of its input without overhead information. To reduce annoying granular noise in the reconstructed image, Lee filter is used after reconstruction in the receiver.