• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.61-64
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• 1992

In this paper, a visual pattern recognition system is proposed, which can recognize both a pattern and its location. This system, referred to as the expanded neocognitron, has the following capabilities: (1) A higher performance in extraction of features, and (2) A new capability for recognizing the locations of patterns. This system adopts the learning and recognizing mechanism of the neocognitron. First, the ability to classify pattern is enhanced by improving the mechanisms of feature extraction and learning algorithm. Second, the function of detecting the location of each pattern is realized by developing an architecture which does not reduce structure, i.e., the unit density is constant all the way from the input stage to the output stage.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.530-533
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• 1995

This paper deals with the problem of motion planning for a unicycle-like robot. We present a simple local planner for unicycle model, based on an approximation of the desired configuration generated by local holonomic planner that ignores motion constraints. To guarantee a collision avoidance, we propose an inequality constraint, based on the motion analysis with the constant control input and time interval. Consequently, we formulate our problem as the constrained optimization problem and a feedback scheme based on local sensor information is established by simply solving this problem. Through simulations, we confirm the validity and effectiveness of our algorithm.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.125-128
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• 2001

In this paper, we propose a low power Scan-based Built-ln Self Test based on circuit partitioning and pattern suppression using modified test control unit. To partition a CUT(Circuit Under Testing), the MHPA(Multilevel Hypergraph Partition Algorithm) is used. As a result of circuit partition, we can reduce the total length of test pattern, so that power consumptions are decreased in test mode. Also, proposed Scan-based BIST architecture suppresses a redundant test pattern by inserting an additional decoder in BIST control unit. A decoder detects test pattern with high fault coverage, and applies it to partitioned circuits. Experimental result on the ISCAS benchmark circuits shows the efficiency of proposed low power BIST architecture.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.805-808
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• 1999

In this paper, a chattering alleviation ISM speed controller for the sinusoidal type BIDC motor is designed. Dead Zone function is proposed to change the chattering occurring in the transient state form high frequency to low frequency and time-varying gains are applied for the control input to eliminate the steady state excessive chattering in the conventional ISM. The proposed Dead Zone function represents the sliding layer composed of two switching surfaces and if a state vector exists in this layer, the chattering don’t occur. Simulation and experimental results confirm the useful effects of the above algorithm.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.732-735
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• 1999

A GA-based optimization technique is adopted in the paper to obtain optimal future control inputs for predictive control systems. For reliable future predictions of a process, we identify the underlying process with an NNARX model structure and investigate to reduce the volume of neural network based on the Lipschitz index and a criterion. Since most industrial processes are subject to their constraints, we deal with the input-output constraints by modifying some genetic operators and/or using a penalty strategy in the GAPC. Some computer simulations are given to show the effectiveness of the GAPC method compared with the adaptive GPC algorithm.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.397-400
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• 1999

As the result of enhancement of CAD, Design Automation and manufacturing technology, it's on the increasing complexity, integration ratio, data signals, and pin count to IC chips. This brings about difficulties of testing, and incresing test time. Now One of the most cost-consuming procedure as integration ratio increases is the testing step. In this paper, we propose a new method, “Efficient TP(test point) assignment algorithm” using “input grouping”, This is helpful method to reducing test length without losing fault coverage. Experimental results show that proposed method reduces test length remarkably and doesn't miss fault coverage, with low hardware overhead Increasing.

• Journal of the Korean Institute of Telematics and Electronics
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• v.18 no.3
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• pp.35-41
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• 1981

In this paper, the application of model reference adaptive control theory to the D.C motor speed control using the microprocessor is studied. It is shown that with the use of an adaptive control algorithm the error between output of the motor and the reference model, which is approximated to first order, can be conve to zero. By computer simulation and the practical implementation with the microprocessor M 6800, can be concluded that the adaptive control system adapts well to the rapid change of the load and reference inputs.

• Journal of Sensor Science and Technology
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• v.20 no.3
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• pp.151-155
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• 2011

A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.7-12
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• 1990

In this paper, we propose a new manipulator control scheme based on the CMAG neural network. The proposed control consists of two components. The feedforward component is an output of trained CMAC neural network and the feedback component is a modified sliding mode control. The CMAC accepts the position, velocity and acceleration of manipulator as input and outputs two values for the controller : One is the nominal torque used for feedforward compensation(M1 network) and the other is the inertia matrix related information used for the feedback component(M2 network). Since the used control algorithm guarantees the robust trajectory tracking in spite of modeling errors, the CMAC mapping errors due to the memory limitation are little worth consideration.

• Journal of Platform Technology
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• v.6 no.1
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• pp.3-8
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• 2018

This paper proposes a technique for recognizing online handwritten cursive data obtained by tracing a motion trajectory while a user is in the 3D space based on a convolution neural network (CNN) algorithm. There is a difficulty in recognizing the virtual character input by the user in the 3D space because it includes both the character stroke and the movement stroke. In this paper, we divide syllable into consonant and vowel units by using labeling technique in addition to the result of localizing letter stroke and movement stroke in the previous study. The coordinate information of the separated consonants and vowels are converted into image data, and Korean handwriting recognition was performed using a convolutional neural network. After learning the neural network using 1,680 syllables written by five hand writers, the accuracy is calculated by using the new hand writers who did not participate in the writing of training data. The accuracy of phoneme-based recognition is 98.9% based on convolutional neural network. The proposed method has the advantage of drastically reducing learning data compared to syllable-based learning.