• The Transactions of the Korean Institute of Electrical Engineers B
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• 제52권11호
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• pp.577-585
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• 2003

This paper proposes a new speed sensorless control method of a permanent magnet synchronous motor using an instantaneous reactive power. In the proposed algorithm, the line currents are estimated by a observer and the estimated speed can be yielded from the voltage equation because the information of speed is included in back emf. But the speed estimation error between the estimated and the real speeds is occured by errors due to measuring the motor parameters and sensing the line current and the input voltage. To minimize the speed estimation error, the estimated speed is compensated by using an instantaneous reactive power. In this paper, the proposed algorithm is not affected by mechanical motor parameters because the mechanical equation is not used. The effectiveness of algorithm is confirmed by the experiments.

• Journal of the Korean Institute of Telematics and Electronics B
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• 제31B권7호
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• pp.119-128
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• 1994

In this paper, we propose a method for facial feature extraction and recognition algorithm using neural networks. First we extract a face part from the background image based on the knowledge that it is located in the center of an input image and that the background is homogeneous. Then using vertical and horizontal projections. We extract features from the separated face image using knowledge base of human faces. In the recognition step we use the back propagation algorithm of the neural networks and in the learning step to reduce the computation time we vary learning and momentum rates. Our technique recognizes 6 women and 14 men correctly.

• Journal of the Korean Institute of Telematics and Electronics
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• 제25권2호
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• pp.102-108
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• 1988

In this paper, a channel routing algorithm which considers cycle problem is proposed. The requirements of routing is given by pin numbers which imply interconnections between a upper block and lower block of the channel. Output is represented by interconnections among equipotential pins. When input is given, the algorithm constructs a channel representation graph and makes weight of each net. And then it checks cycle and finidhes the routing. If the cycle is detected, it finds path with maze routing. This algorithm have coded in C language on IBM-PC /AT. If cycle is not detected, the results are near optimal values. If it is detected, routing is possible as well.

• Journal of the Korean Institute of Telematics and Electronics
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• 제27권1호
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• pp.30-36
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• 1990

Context-free language can be recognized by Cocke-Younger-Kasami algorithm. This algorithm is a class of polyadic-nonserial dynamic programming technique and has the O(n**3) time complexity. In this paper, a one-dimensional systolic array for recognition of context-free language is designed. The designed triangle type two-dimensional array is projected and transformed to an one-dimensional array. The designed one-dimensional array has n processing elements and \ulcornern+1)/2\ulcorner(n-1)+3n-1 time units to process the algorithm (n is the length of input string). The time complexity is O(n\ulcorner.

• Proceedings of the KIEE Conference
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2383-2385
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• 2000

It is proposed a new algorithm for a neural network adaptive tracking control scheme to improve performance in this paper. In supervisory control scheme, the upper and lower bound of the parameters are directly estimated by using RBF neural network without their information, and the weighting parameters of the control input are adjusted on-line by adaptation laws. As a result, the proposed algorithm assured that the output errors go to zero without relation to existing minimum approximation errors and disturbances. The effectiveness of the proposed algorithm is demonstrated through the simulation of one-link rigid robotics manipulator.

• Journal of the Korean Institute of Telematics and Electronics B
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• 제33B권9호
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• pp.97-106
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• 1996

In this paper, we propose a face recognition algorithm using the hidden markov model and neural networks (HMM-NN). In the preprocessing stage, we find edges of a face using the locally adaptive threshold (LAT) scheme and extract features based on generic knowledge of a face, then construct a database with extracted features. In the training stage, we generate HMM parameters for each person by using the forward-backward algorithm. In the recognition stage, we apply probability vlaues calculated by the HMM to subsequent neural networks (NN) as input data. Computer simulation shows that the proposed HMM-NN algorithm gives higher recognition rate compared with conventional face recognition algorithms.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2007년도 하계종합학술대회 논문집
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• pp.261-262
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• 2007

This paper proposes a new IFFT(Inverse Fast Fourier Transform) algorithm, which is proper for IMDCT(Inverse Modified Discrete Cosine Transform) of MPEG-2 AAC(Advanced Audio Coding) decoder. The IFFT used in $2^N$-point IMDCT employ the bit-reverse data arrangement of inputs and N/4-IFFT to reduce the calculation cycles. We devised a new data arrangement algorithm of IFFT input and N/$4^{n+1}$-IFFT and can reduce multiplication cycles, addition cycles, and ROM size.

• Journal of Satellite, Information and Communications
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• 제7권1호
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• pp.33-38
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• 2012

In this paper we proposed an algorithm selection method based on the features of video inputs which are acquired from the large scale integrated surveillance system. The example of integrated surveillance system is the metro railway system. Automated surveillance system at large area saves the human resource and minimizes the non-observing spots. We have analyzed the input video under this system in order to apply adequate video analytics algorithms in each installing places and for each situation. Based on the analysis, we suggested event processing scenarios and video analytic algorithm selection.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제16권1호
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• pp.33-40
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• 2012

This paper proposes a method to implement biological early warning systems(BEWS). This system generates periodically data event using a monitoring daemon and it extracts the feature parameters from this data sets. The feature parameters are derived with 6 variables, x/y coordinates, distance, absolute distance, angle, and fractal dimension. Specially by using the fractal dimension theory, the proposed algorithm define the input features represent the organism characteristics in non-toxic or toxic environment. And to find a moderate algorithm for learning the extracted feature data, the system uses an extended learning algorithm(UChoo) popularly used in machine learning. And this algorithm includes a learning method with the extended data expression to overcome the BEWS environment which the feature sets added periodically by a monitoring daemon. In this algorithm, decision tree classifier define class distribution information using the weight parameter in the extended data expression. Experimental results show that the proposed BEWS is available for environmental toxicity detection.

• Journal of information and communication convergence engineering
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• 제8권5호
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• pp.575-580
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• 2010

Eye gaze as a form of input was primarily developed for users who are unable to use usual interaction devices such as keyboard and the mouse; however, with the increasing accuracy in eye gaze detection with decreasing cost of development, it tends to be a practical interaction method for able-bodied users in soon future as well. This paper explores a low-cost, robust, rotation and illumination independent eye gaze system for gaze enhanced user interfaces. We introduce two brand-new algorithms for fast and sub-pixel precise pupil center detection and 2D Eye Gaze estimation by means of deformable template matching methodology. In this paper, we propose a new algorithm based on the deformable angular integral search algorithm based on minimum intensity value to localize eyeball (iris outer boundary) in gray scale eye region images. Basically, it finds the center of the pupil in order to use it in our second proposed algorithm which is about 2D eye gaze tracking. First, we detect the eye regions by means of Intel OpenCV AdaBoost Haar cascade classifiers and assign the approximate size of eyeball depending on the eye region size. Secondly, using DAISMI (Deformable Angular Integral Search by Minimum Intensity) algorithm, pupil center is detected. Then, by using the percentage of black pixels over eyeball circle area, we convert the image into binary (Black and white color) for being used in the next part: DTBGE (Deformable Template based 2D Gaze Estimation) algorithm. Finally, using DTBGE algorithm, initial pupil center coordinates are assigned and DTBGE creates new pupil center coordinates and estimates the final gaze directions and eyeball size. We have performed extensive experiments and achieved very encouraging results. Finally, we discuss the effectiveness of the proposed method through several experimental results.