Hyeon-Deok Bae

A Filter Bank and a Self-Tuning Adaptive Filter for the Harmonic and Interharmonic Estimation in Power Signals

We present a method that combines a filter bank (FB) system with adaptive filtering to estimate parameters describing the harmonics and the interharmonics present in power signals. The proposed method decomposes the input power signal using an FB system that is a modular binary tree structure with the fundamental FBs arranged successively in each stage. The fundamental FB is designed to separate the odd and even harmonics to reduce spectral leakage. An adaptive filter is used to improve the accuracy of parameter estimation for each decomposed harmonic. Parameters describing the interharmonic components are estimated from the error signal of the adaptive filter, which is self-tuning. The estimation of the amplitude and frequency of each of the harmonic and interharmonic components is done recursively. Computer simulations were performed on synthesized signals to assess the performance of the method.

Subband affine projection algorithm for acoustic echo cancellation system

We present a new subband affine projection (SAP) algorithm for the adaptive acoustic echo cancellation with long echo path delay. Generally, the acoustic echo canceller suffers from the long echo path and large computational complexity. To solve this problem, the proposed algorithm combines merits of the affine projection (AP) algorithm and the subband filtering. Convergence speed of the proposed algorithm is improved by the signal-decorrelating property of the orthogonal subband filtering and the weight updating with the prewhitened input signal of the AP algorithm. Moreover, in the proposed algorithms, as applying the polyphase decomposition, the noble identity, and the critical decimation to subband the adaptive filter, the sufficiently decomposed SAP updates the weights of adaptive subfilters without a matrix inversion. Therefore, computational complexity of the proposed method is considerably reduced. In the SAP, the derived weight updating formula for the subband adaptive filter has a simple form as ever compared with the normalized least-mean-square (NLMS) algorithm. The efficiency of the proposed algorithm for the colored signal and speech signal was evaluated experimentally.

Walking Number Detection Algorithm using a 3-Axial Accelerometer Sensor and Activity Monitoring

The research for a 3-axial accelerometer sensor has increased dramatically in the fields of cellular phone, PDA, etc. In this paper, we develop a human walking detection algorithm using 3-axial accelerometer sensor and a user interface system to show the activity expenditure in real-time. To measure a walking number more correctly in a variety of walking activities including walking, walking in place, running, slow walking, we propose a new walking number detection algorithm using adaptive threshold value. In addition, we calculate the activity expenditure base on counted walking number and display calculated activity expenditure on UI in real-time. From the experimental results, we could obtain that the detection rate of proposal algorithm is higher than that of existing algorithm using a fixed threshold value about . Especially, it could be found out high detection rate in walking in place.

Time varying harmonics estimation of power signal based on filter banks and adaptive filtering

This paper proposes a new method which combines filter bank system and adaptive filtering for the parameters estimation of the harmonics and the interharmonics of power signals. The proposed method decomposes the input power signal by designing the filter bank system. This filter bank has binary tree structure, and uses the fundamental filter banks successively in each decomposing stage. The fundamental filter bank separates the odd harmonic and the even harmonic components to reduce the spectral leakage. The adaptive filter is applied to the each harmonic component for the accurate parameter estimation. And the interharmonic component parameters are estimated through the error signal of the adaptive filter. The amplitudes and the frequency estimation of the each harmonic and interharmonic are carried out by the recursive method. To demonstrate the performance of the method, computer simulations are performed to the synthesized signals.

Adaptive beamforming for moving array with 3-axis electronic compass in hearing aids

People who use digital hearing aids with directional microphones want to listen target sounds selectively, whether the speaker is remote or nearby. We have proposed a steerable microphone array technique that combines omnidirectional and directional microphone signals with 3-axis electronic compass. When the user moves the array toward a desired sound source, the microphone array can be steered while fast and slow head movements. The 3-axis electronic compass can be built in hearing aids to generate coordinates of a microphone in array. When array moves, the adaptive beamformer uses the geometry information to find optimal solution for enhancing the sound quality such as Speech Intelligibility.

Extraction of Rotating Machine Sources for Fault Diagnostics using Independent Component Analysis

In this paper we introduce the use of independent component analysis for extraction of machine signal from noisy measurements. ts. The presence of interference noise at the machine defect sificationlas- ification cause misclassification. Consequently, we present a flexible method using the independent component analysis with subband analysis sis for extraction of rotating sources. The proposed method utilizes ICA estimation of unifying structure, includes mutual information and time structure. If the signals have no time correlation, their complexity ty may be achieved by their entropies. We introduce an on-linegorithm,al- ithm, such as an alternative of the algorithm that includes mutual information and time-correlation. Simulation study shows that the combined scheme can effectively extract the signal of interest from the instantaneous and delayed mixtures with noise, in comparison with the conventional method and the proposed approaches. The performance ance of the proposed method is evaluated experimentally on aingbear- ng test bed data using the proposed method and the results show to provide more accurate defect analysis with noisy corrupted data over the conventional method.

Pedestrian navigation system with fall detection and energy expenditure calculation

In this paper, a mobile node which includes a 3-axis accelerometer, a 2-axis gyroscope, and two digital compasses is implemented and evaluated to obtain the position, fall detection and activity energy expenditure calculation. The position can be found using steps and heading detected from the accelerometer and digital compasses. Fall is detected by analysis of the sensing patterns obtained from accelerometer and gyroscope. Activity energy expenditure can be calculated with activity count derived from accelerometer and a predefined regression equation. The obtained information from the implemented mobile node is transmitted to a monitoring station using ZigBee wireless communication in real time. Experimental results show the effectiveness of the proposed methods.

Subband Adaptive Filtering with Maximal Decimation Using an Affine Projection Algorithm

Affine projection algorithms perform well for acoustic echo cancellation and adaptive equalization. Although these algorithms typically provide fast convergence, they are unduly complex when updating the weights of the associated adaptive filter. In this paper, we propose a new subband affine projection (SAP) algorithm and a facile method for its implementation. The SAP algorithm is derived by combining the affine projection algorithm and the subband adaptive structure with the maximal decimation. In the proposed SAP algorithm, the derived weight-updating formula for the subband adaptive filter has a simple form as compared with the normalized least mean square (NLMS) algorithm. The algorithm gives improved convergence and reduced computational complexity. The efficiency of the proposed algorithm for a colored input signal is evaluated experimentally.

Home healthcare self-monitoring system for chronic diseases

With rapid aging and economic growth, people are becoming more interested in their long-term health and wellness. In this paper, we implement a home self healthcare monitoring system which can monitor respiration, blood glucose, urinary flow, and temperature. The obtained bio-signal by the each sensing unit is transmitted to a monitoring station using Zigbee wireless communication in real time at home on the personal computer.

Design and Implementation of Seismic Data Acquisition System using MEMS Accelerometer

In this paper, we design a seismic data acquisition system(SDAS) and implement it. This system is essential for development of a noble local earthquake disaster preventing system in population center. In the system, we choose a proper MEMS-type triaxial accelerometer as a sensor, and FPGA and ARM processor are used for implementing the system. In the SDAS, each module is realized by Verilog HDL and C Language. We carry out the ModelSim simulation to verify the performances of important modules. The simulation results show that the FPGA-based data acquisition module can guarantee an accurate time-synchronization for the measured data from each axis sensor. Moreover, the FPGA-ARM based embedded technology in system hardware design can reduce the system cost by the integration of data logger, communication sever, and facility control system. To evaluate the data acquisition performance of the SDAS, we perform experiments for real seismic signals with the exciter. Performances comparison between the acquired data of the SDAS and the reference sensor shows that the data acquisition performance of the SDAS is valid.