• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.9
• /
• pp.909-917
• /
• 1992

This paper proposes the realization of state-space digital filters with minimum output error variance. The algorithm is transforms of controllability and observability gramian in linear time invariant systems by weighted function and can improve performance of the digital filters by reducing the put error variance for state space coeffient variation. A numerical example shows that algorithm structure has much lower output error variance than that of other four structures(canonical, parallel, statistical sensitivity, balanced).

• Korean Journal of Computational Design and Engineering
• /
• v.8 no.4
• /
• pp.262-269
• /
• 2003

An approach to compute characteristic curves such as section curves, reflection characteristic lines, and asymptotic curves on a surface is introduced. Each problem is formulated as a surface-plane inter-section problem. A single-valued function that represents the characteristics of a problem constructs a property surface on parametric space. Using a contouring algorithm, the property surface is intersected with a horizontal plane. The solution of the intersection yields a series of points which are mapped into object space to become characteristic curves. The approach proposed in this paper eliminates the use of traditional searching methods or non-linear differential equation solvers. Since the contouring algorithm has been known to be very robust and rapid, most of the problems are solved efficiently in realtime for the purpose of visualization. This approach can be extended to any geometric problem, if used with an appropriate formulation.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.9
• /
• pp.49-61
• /
• 1996

Back-propagation(BP) algorithm needs a lot of time to train the artificial neural network (ANN) to get high accuracy level in classification tasks. So there have been extensive researches to process back-propagation algorithm on parallel processors. This paper prsents a linear systolic array which calculates forward-backward propagation of BP algorithm at the same time using effective space-time transformation and PE structure. First, we analyze data flow of forwared and backward propagations and then, represent the BP algorithm into data dapendency graph (DG) which shows parallelism inherent in the BP algorithm. Next, apply space-time transformation on the DG of ANN is turn with orthogonal direction projection. By doing so, we can get a snakelike systolic array. Also we calculate the interval of input for parallel processing, calculate the indices to make the right datas be used at the right PE when forward and bvackward propagations are processed in the same PE. And then verify the correctness of output when forward and backward propagations are executed at the same time. By doing so, the proposed system maximizes parallelism of BP algorithm, minimizes th enumber of PEs. And it reduces the execution time by 2 times through making idle PEs participate in forward-backward propagation at the same time.

• Proceedings of the KIEE Conference
• /
• 2003.10b
• /
• pp.66-68
• /
• 2003

This paper is deal with the method of design for the optimum model using genetic algorithms in slotted Permanent Magnet Linear Synchrous Motor (PMLSM). The objective functions are maximum thrust and minimum detent force. Characteristic analysis method is used 2D space harmonic analysis method. Design parameters are PM width, PM height and slot width.

• Journal of KIISE:Computer Systems and Theory
• /
• v.31 no.1_2
• /
• pp.10-18
• /
• 2004

Quadtree, which is a hierarchical data structure, is a very important data structure to represent binary images. The linear quadtree representation as a way to store a quadtree is efficient to save space compared with other representations. Therefore, it has been widely studied to develop efficient algorithms to execute operations related with quadtrees. The operations of unaligned linear quadtrees, which are operations among the linear quadtrees with different origin, are able to perform the translated or rotated images efficiently. And this operations requires alignment of the linear quadtrees. In this paper, we present an efficient algorithm to perform alignment of unaligned linear quadtrees, using three-dimensional $n{\pm}n{\pm}n$ processors on RMESH(Reconfigurable MESH). This algorithm has constant-time complexity by using efficient basic operations to route the locational codes of quardtree on the hierarchical structure of $n{\pm}n{\pm}n$ RMESH.

• The KIPS Transactions:PartA
• /
• v.10A no.3
• /
• pp.207-214
• /
• 2003

Quadtree, which is a hierarchical data structure, is a very important data structure to represent binary images. The linear quadtree representation as a way to store a quadtree is efficient to save space compared with other representations. Therefore, it has been widely studied to develop efficient algorithms to execute operations related with quadtrees. The linear translation is one of important operations in image processing, which moves the image by a given distance. In this paper, we present an algorithm to perform the linear translation of binary images represented by quadtrees, using three-dimensional $n{\times}n{\times}n$ processors on RMESH (Reconfigurable MESH). This algorithm has constant-time complexity by using efficient basic operations to route the locational codes of quardtree on the hierarchical structure of n${\times}$n${\times}$n RMESH.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.2
• /
• pp.911-917
• /
• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• Journal of Communications and Networks
• /
• v.10 no.1
• /
• pp.44-54
• /
• 2008

In this paper, an iterative multiple symbol differential detection for turbo coded differential unitary space-time modulation using a posteriori probability (APP) demodulator is investigated. Two approaches of different complexity based on linear prediction are presented to utilize the temporal correlation of fading for the APP demodulator. The first approach intends to take account of all possible previous symbols for linear prediction, thus requiring an increase of the number of trellis states of the APP demodulator. In contrast, the second approach applies Viterbi algorithm to assist the APP demodulator in estimating the previous symbols, hence allowing much reduced decoding complexity. These two approaches are found to provide a trade-off between performance and complexity. It is shown through simulation that both approaches can offer significant BER performance improvement over the conventional differential detection under both correlated slow and fast Rayleigh flat-fading channels. In addition, when comparing the first approach to a modified bit-interleaved turbo coded differential space-time modulation counterpart of comparable decoding complexity, the proposed decoding structure can offer performance gain over 3 dB at BER of $10^{-5}$.

• Korean Journal of Microbiology
• /
• v.34 no.1_2
• /
• pp.58-63
• /
• 1998

Fragment assembly problem is to reconstruct DNA sequence contigs from a collection of fragment sequences. We have developed an efficient X-window program, XFAP, for assembling DNA fragments. In the XFAP, the dimer frequency comparison method is used to quickly eliminate pairs of fragments that can not overlap. This method takes advantage of the difference of dimer frequencies within the minimum acceptable overlap length in each fragment pair. Hirschberg algorithm is applied to compute the maximal-scoring overlapping alignment in linear space. The perfomance of XFAP was tested on a set of DNA fragment sequences extracted from long DNA sequences of GenBank by a fragmentation program and showed a great improvement in execution time, especially as the number of fragments increases.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.2
• /
• pp.204-210
• /
• 2005

This paper presents online identification algorithm for TSK fuzzy model. The proposed algorithm identify structure of premise part by using distance, and obtain the parameters of the piecewise linear function consisting consequent part by using recursive least square. Only input space was considered in Most researches on structure identification, but input and output space is considered in the proposed algorithm. By doing so, outliers are excluded in clustering effectively. The existing other algorithm has disadvantage that it is sensitive to noise by using data itself as cluster centers. The proposed algorithm is non-sensitive to noise not by using data itself as cluster centers. Model can be obtained through one pass and it is not needed to memorize many data in the proposed algorithm.