• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.9
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• pp.795-805
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• 2012

This paper proposes an algorithm and a hardware architecture for a broadcast communication which has the worst bottleneck among multiprocessor using distributed memory architectures. In conventional system, The pipelined broadcast algorithm is an algorithm which takes advantage of maximum bandwidth of communication bus. But unnecessary synchronization process are repeated, because the pipelined broadcast sends the data divided into many parts. In this paper, the MPI unit for pipeline chain algorithm based on circuit switching removing the redundancy of synchronization process was designed, the proposed architecture was evaluated by modeling it with systemC. Consequently, the performance of the proposed architecture was highly improved for broadcast communication up to 3.3 times that of systems using conventional pipelined broadcast algorithm, it can almost take advantage of the maximum bandwidth of transmission bus. Then, it was implemented with VerilogHDL, synthesized with TSMC 0.18um library and implemented into a chip. The area of synthesis results occupied 4,700 gates(2 input NAND gate) and utilization of total area is 2.4%. The proposed architecture achieves improvement in total performance of MPSoC occupying relatively small area.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.3
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• pp.61-67
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• 2001

In this paper, a method that apply LP algorithm to image for speech recognition is suggested, using both speech and image information for recogniton of korean numeral speech. The input speech signal is pre-emphasized with parameter value 0.95, analyzed for B th LP coefficients using Hamming window, autocorrelation and Levinson-Durbin algorithm. Also, a gray image signal is analyzed for 2-dimensional LP coefficients using autocorrelation and Levinson-Durbin algorithm like speech. These parameters are used for input parameters of neural network using back-propagation algorithm. The recognition experiment was carried out at each noise level, three numeral speechs, '3','5', and '9' were enhanced. Thus, in case of recognizing speech with 2-dimensional LP parameters, it results in a high recognition rate, a low parameter size, and a simple algorithm with no additional feature extraction algorithm.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.453-459
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• 2008

The neural network is currently being used throughout numerous control system fields. However, it is not easy to obtain an input-output pattern when the neural network is used for the system of a single feedback controller and it is difficult to obtain satisfactory performance with when the load changes rapidly or disturbance is applied. To resolve these problems, this paper proposes a new mode to implement a neural network controller by installing a real object for control and an algorithm for this, which can replace the existing method of implementing a neural network controller by utilizing activation function at the output node. The real plant object for controlling of this mode implements a simple neural network controller replacing the activation function and provides the error back propagation path to calculate the error at the output node. As the controller is designed using a simple structure neural network, the input-output pattern problem is solved naturally and real-time learning becomes possible through the general error back propagation algorithm. The new algorithm applied neural network controller gives excellent performance for initial and tracking response and shows a robust performance for rapid load change and disturbance, in which the permissible error surpasses the range border. The effect of the proposed control algorithm was verified in a test that controlled the speed of a motor equipped with a high speed computing capable DSP on which the proposed algorithm was loaded.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.11
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• pp.1701-1713
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• 1993

This paper proposes a simple and highly effective RACMC(Real-time ATM Cell Monitoring and Control) algorithm and the resulting bandwidth gain effects art considered. RACMC algorithm performs usage parameter controls according to the monitoring informations of input data cells generated from the accepted connections and the controlling informations set by the M/P(Management Plane) for that connection. The results of monitoring and controlling actions for ATM data cells are transmitted to the M/P and the control parameters in lookup table are updated according to the condition of currently used bandwith. Therefore, the proposed algorithm can allocate network resource optimally and solve the several tantalizing problems that the existing cell control algorithm have, that is, the difficulty in controlling as monitoring very bursty traffics, unavoidable processing delay, and limited input buffer size when implemented. By the performance analysis using computer simulation, RACMC algorithm proves to be very effective especially in ATM network as implemented simply.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1545-1550
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• 2021

We propose an optimal variable step size adjustment method for the simplified subband affine projection algorithm (Simplified SAP; SSAP) in a subband structure based on a polyphase decomposition technique. The proposed method provides an optimal step size derived to minimize the mean square deviation(MSD) at the time of updating the coefficients of the subband adaptive filter. Application of the proposed optimal step size in the SSAP algorithm using colored input signals ensures fast convergence speed and small steady-state error. The results of computer simulations performed using AR(2) signals and real voices as input signals prove the validity of the proposed optimal step size for the SSAP algorithm. Also, the simulation results show that the proposed algorithm has a faster convergence rate and good steady-state error compared to the existing other adaptive algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.784-788
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• 2008

In this research, we propose a remote speech input unit, a new method of user-friendly speech input in speech recognition system. We focused the user friendliness on hands-free and microphone independence in speech recognition applications. Our module adopts two algorithms, the automatic speech detection and speech enhancement based on the microphone array-based beamforming method. In the performance evaluation of speech detection, within-200msec accuracy with respect to the manually detected positions is about 97percent under the noise environments of 25dB of the SNR. The microphone array-based speech enhancement using the delay-and-sum beamforming algorithm shows about 6dB of maximum SNR gain over a single microphone and more than 12% of error reduction rate in speech recognition.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.199-210
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• 1994

Most of clustering methods usually employ a center or predefined shape of a cluster to assign the input data into the cluster. When there is no information about data set, it is impossible to predict how many clusters are to be or what shape clusters take. (the shape of clusters could not be easily represented by the center or predefined shape of clusters) Therefore, it is difficult to assign input data into a proper cluster using previous methods. In this paper, to overcome such a difficulty a cluster is to be represented as a collection of several subclusters representing boundary of the cluster. And membership functions are used to represent how much input data bllongs to subclusters. Then the position of the nearest subcluster is adaptively corrected for expansion of cluster, which the subcluster belongs to by use of a competitive learning neural network. To show the validity of the proposed method a numerical example is illustrated where FMMC(Fuzzy Min-Max Clustering) algorithm is compared with the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2470-2476
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• 1997

We propose a simle scheme for detecting tone signals narrowly spaced in the frequency by employing a nonlinear device called Teager's energy tracker. When the input signal is a tone signal, the output of Teager's energy tracker is proportional to the energy and tone frequency of the input signal. When the envelope of the input tone is varying, this tracker can also track the energy of the envelope. By employing Teager's algorithm as a preprocessor, the detector for narrowly spaced tone signals can be implemented without the use of sharp notch filters. As an example, the proposed detector is applied to distinguishing ITU-T V.8 and V.25 tone signals. The detector perfodrmance is analyszed and is verified by computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.11
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• pp.3001-3011
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• 1996

In this paper, using DBNN algorithm which is used in the binary pattern classification or speech signal processing the digital DBNN circuit is designed having the variable expansion depending the size of input data and pattern type. The processing elemen(PE) of the proposed network consists of the synapse and MAXNET circuits for the similarity measurement between reference and input pattern. Global MAXNET selects the global winner among the local winners which is selected in each PE. Through the several simultions, and thus each PE and global MAXNET search the reference pattern that was the most simlar to input pattern for the discord of the pattern.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.675-683
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• 1996

CAC, UPC, NPC, cell level QoS and congestion control is required to assign efficiently channels's BW and to prevent networks from congestion. In the CAC algorithm, each user defines characteristics of input traffic when channels are set up and network based on this parameters determines the acception or rejection of the required BW. The CAC control mechanism is classified into the centralized BW allocation mechanism and the distributed BW Allocation mechanism according to the function and position of CAC processor allocating BW. In this paper, in contrast with esisted the distributed BW allocation mechanism which assumes the required BW of input traffic as constant, we assume input traffic & serices as bulk probability distribution in order to analyze performance more precisely.