• Journal of the Institute of Convergence Signal Processing
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• v.3 no.4
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• pp.62-66
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• 2002

An attempt of using SOCMAC neural network for the prediction of a nonlinear sequence, which is generated by Mackey-Glass equation, is reported. The ,report shows the SOCMAC can handle a system with multi-dimensional continuous inputs, which has been considered very difficult, if not impossible, task to be implemented by a CMAC neural network because of a huge amount of memory required. Also, an improved training method based on the variable receptive fields is proposed. The Performance ranged somewhere around those of TDNN and BP neural networks.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.38-41
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• 2003

There are many kinds of algorithms used for the purpose of data mining. But without the understanding the underlying principles in the algorithm, the result of the data mining cannot be interpreted correctly. In this paper, the principle of ID3 algorithm is explained for that purpose. In addition, the way how to generate good training examples from the relational database is treated, as well as how to convert continuous values into discrete values is considered to use the algorithm for the data mining of real world database.

• Journal of Navigation and Port Research
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• v.28 no.2
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• pp.135-140
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• 2004

A purpose of developing a sound source tracking system in this paper is to reduce the noise efficiently from the received signal by microphone array and measure the signal's time delay between the microphones. I have applied the wavelet analysis algorithm to the system and calculated the sound source's relative position For the performance evaluation, I have compared with the results of utilizing the digital filtering methods based on the FIR LPF using Kaiser window function and the inverse Chebyshev IIR LPF. As a result, I have confirmed the fact that 'time-scale' filter using inverse discrete wavelet transform was suitable for this system.

• The Journal of Information Technology
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• v.9 no.1
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• pp.9-19
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• 2006

Medications or conitive-behavior methods have been mainly used as a treatment of alcoholism. lately the virtualy technology has been applied to the kink of alcoholic disorders. A virtual environment makes him having avility to over come the drink. In this study, we were implemented by making panorama images and 3D object modules using 3D MAX, VRML, JAVA. And the BAR stimulator that composed with a position sensor, head mount display, and audio system, is suggested. To illustrate the physiological difference between a person who has a alcoholism and without a liquor bottle, heart rate was measured during experiment, and also measured a person's HR after the virtual reality training. The system measures the Physiological signals such as ECG, Temperature, analyzes those data automatically. The system has two parts, one is physiological data acquisition part which gets the body signal, and the other one is mobile nuit which includes signal processing and transmission functions, And Bluetooth allows two parts to communicate with each other. we demonstrated the subjective effectiveness of virtual reality psychotherapy through the clinical experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.327-329
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• 2021

Underwater acoustic communication channel is influenced by environmental parameters such as multipath, background noise and scattering. Therefore, a transmitted signal is influenced by the sea surface and the sea bottom boundaries, and a received signal shows a delay spread. These factors create a noise in the image and degrade the quality of underwater acoustic communication. To solve these problems, in this paper, we evaluate the performance of an underwater acoustic communication model using a denoising auto-encoder used for unsupervised learning. Noise images generated by the underwater multipath channel were collected and used as training data. Experimental results were analyzed as a PSNR parameter that expressed the noise ratio of the two images.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.10
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• pp.923-929
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• 2004

In this research, Forced Vibration Test(FVT) on a cable stayed bridge was conducted to examine the validity of the frequency domain pattern recognition method using signal anomaly index and artificial neuralnetwork. 7he considering structure, Samchunpo Bridge, located in Sachun-Shi, Kyungsangnam-Do, is a cable stayed bridge with the 436 meter span. The excitation force was induced by a sudden braking of a fully loaded truck. and vortical acceleration signals were acquired at 14 points. The initial 2-dimensional FE-model was developed from the design documents to prepare the training sets for the artificial neural network, and then the model calibration was performed with the field test data. As a result of the model calibration, we obtained the FFT spectrums from the model simulation, which was similar to those from the vibration test. These tests and the simulation data will be used for the structural identification using arbitrarily added masses to the bridge.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.619-623
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• 2003

In this research, Forced Vibration Test(FVT) on a cable stayed bridge was conducted to examine the validity of the frequency domain pattern recognition method using signal anomaly index and artificial neural network. The considering structure, Samchunpo Bridge, located in Sachun-Shi, Kyungsangnam-Do, is a cable stayed bridge with the 436 meter span. The excitation force was induced by a sudden braking of a fully loaded truck, and vertical acceleration signals were acquired at 14 points. The initial 2-dimensional FE-model was developed from the design documents to prepare the training sets for the artificial neural network, and then the model calibration was performed with the field test data. As a result of the model calibration, we obtained the FFT spectrums from the model simulation, which was similar to those from the vibration test. These tests and the simulation data will be used fur the structural identification using arbitrarily added masses to the bridge.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.683-686
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• 2002

It is fundamental to count and pack the pills in the medicine manufacture field but those tasks are time and labor consuming. Thus, the need fur automation of those tasks is necessarily getting increased in order to get effective mass production. It Is significant to perceive pills quickly and precisely. There were many trials for this processing but the performance of the existing counting machines varies about size, shape and dispersion tendency of pills. In this paper, the authors try to improve the counting performance of a pill counting machine that has optical sensors with the neural network. The passing signal of pill is acquired with optical sensor and the passage signal of the pill is extracted as input patterns. The gradient and integration of signal during passing time and the time keeping the pill interrupt the light from the LED are used as characteristic feature. The back propagation and perception algorithm are used for training. Experimental results with several pills show that the designed algorithm is a little bit effective to reduce the noise effect which is generated from interference among the machine components and unreliable environment.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.285-288
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• 2001

In this paper, we proposed new method of speech feature extraction using ICA(Independent Component Analysis) which minimized the dependency and correlation among speech signals on purpose to separate each component in the speech signal. ICA removes the repeating of data after finding the axis direction which has the greatest variance in input dimension. We verified improvement of speech recognition ability with training and recognition experiments when ICA compared with conventional mel-cepstrum features using HMM. Also, we can see that ICA dealt with the situation of recognition ability decline that is caused by environmental noise.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.7 no.1
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• pp.39-43
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• 2013

In this paper, we present a effective method of gait rehabilitation training using critical point of median frequency in muscle fatigue analysis using EMG. To target the five healthy volunteers, EMG signal were measured in the quadriceps femoris muscle and the tibialis anterior muscle in order to determine muscle fatigue. We performed a test targeting three adult male for 30 minutes on a treadmill at a speed of 6km/h same. EMG signal analysis in frequency and median frequency is calculated to quantification of muscle fatigue, and calculated the critical point which is saturated by muscle fatigue during 30 minutes. We set saturated point the threshold which muscle can withstand. The results of this paper, we are able to quantify the threshold of the muscle.