• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.3
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• pp.12-23
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• 1997

In this paper, we propose a new cell switch fabric for increasing the performance of ATM switching systems. Proposed switching network consists of a sorting network and a routing network. Both of these are multistage networks where each stage performs a fixed permutation on the incoming lines, and then routes them through a clumn of 2x2 switching elements. It is designed for distributing inputs and parallel processing to reduce the hardware complexity and obtain high performance of switching network. The structure and the operation of th eswitching network aredescribed and the performanceof the switching network is anlyzed under uniform traffic models. In this result, though the size of proposed network is increased the large scale, it has always the same throughput as the that of genral output queueing system with N=2. So, it is found that our proposed network is appropriate for the high apeed and lrger size of ATM switching systems.

• Journal of the Korean Institute of Telematics and Electronics
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• v.13 no.6
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• pp.20-23
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• 1976

A boolean algebra method for computing the reliability in a communication network is prosented. Given the set of all simple paths between two nodes in a network, the terminal reliability can be symbolically computed by the Boolean operation which is named parallel operation. The method seems to be promising for both oriented and nonoriented network.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.5
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• pp.394-403
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• 1991

This paper described the development of input driven multilayer perceptron(IDMLP) neural network and it's application to the Korean spoken digit recognition. The IDMPLP neural network used here and the learning algorithm for this network was proposed newly. In this model, weight value is integer and transfer function in the neuron is hard limit function. According to the result of the network learning for the some kinds of input data, the number of network layers is one or more by the difficulties of classifying the inputs. We tested the recognition of binaried data for the spoken digit 0 to 9 by means of the proposed network. The experimental results are 100% and 96% for the learning data and test data, respectively.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.179-189
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• 1994

A two-phase neural network finds exact feasible solutions for a constrained optimization programming problem. The time-varying programming neural network is a modified steepest-gradient algorithm which solves time-varying optimization problems. In this paper, we propose a time-varying two-phase optimization neural network which incorporates the merits of the two-phase neural network and the time-varying neural network. The proposed algorithm is applied to system identification and function approximation using a multi-layer perceptron. Particularly training of a multi-layer perceptrion is regarded as a time-varying optimization problem. Our algorithm can also be applied to the case where the weights are constrained. Simulation results prove the proposed algorithm is efficient for solving various optimization problems.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.9-18
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• 1997

In this paper, we implemented the communication module in the Telephone Network Access Subsystem(TNAS) of the Advanced Communications Processing System(ACPS). We defined some kinds of communication tasks and related resources like several queues which are executed in real-time operating system, and implemented the procedures for processing the user information. Through traffic modeling and simulation, the performance of the Service Processing board Assembly(SPA) is evaluated in the aspets of system utilization and buffer size. The ACPS should accommodate various public networks such as public switch telephone network, packet switchen data network, frame realy netork, and ATM network. The communications module proposed in this paper could be used inthe interface beween the SPA and the High Speed Network Adaptor of other network interface subsystems.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.10
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• pp.1518-1527
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• 1989

We proposed a technique to design a multimicrocomputer system for real-time parallel processing with an interconnection network which has good network latency time. In order to simplify the performance evaluation and the design procedure under the hard real-time constraints we defined network latency time which takes into account the queueing delays of the networks. We designed a dynamic interconnection network following the proposed technique, and the simulation results show that we can easily estimate the multimicrocomputer system's approximate performance using the defined network latency time before the actual design, so this definition can help the efficient design of the real-time parallel processing systems.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.120-126
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• 1995

The diffusion neural network can be cfficiently applied to the Gaussian processing. For example, a difference of two Gaussians(DOG) is performed by this network with ease. In this paper, we model a neural network to perform the function /t(.del.${\Delta}^{2}$G) by using the diffusion neural network. This model is used to detect the edges of moving target in image. By this model not only moving target is separated from stationary background but also their trajectories are obtained using accumulated past information in the diffusion neural network. Furthermore this model needs a small number of connections per cell and the connection weights are fixed-valued. Therefore its hardware can be easily implemented with simple structure.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.140-148
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• 1996

This paper proposes a combined feedforward/feedback controller which uses jacobians of neural network. The jacobians are calculated form the neural network that identifies the nonlinear plant, which are used for designing a jacobian controller and for training a neural network controller. Normally, it takes much time to train the neural network controller. Combining the neural and the jacobian controller, it can be a stable controller from the beginning of training phase of neural network, and it can be implemented as a learning-while-functioning controller. Simulated resutls for the proposed controller show its effectiveness and better performances.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.148-155
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• 1997

Ths signal processing technqiue of FET type electrolyte sensors using the back propagation neural network was studied to reduce the interference effects of the different electrolytes. The FET-type electrolyte sensors, pH-ISFET, K-ISFET, and Ca-ISFET, were prepared to measure the pH, K, and Ca electrolytes. Neural network consisted of three layers was learned with 8 patterns and 9 patterns. The sensor output obtained with arbitrary concentrations was processed by the learned neural network. The errors obtained from calibration curve for pH, K, and Ca were .+-.0.039 pH, .+-.2.508 mmol/l, and .+-.1.807 mmol/l, respectively, without considering the interference effects. The errors of the network output for pH, K, and Ca were reduced to .+-.0.005 pH, .+-.0.436 mmol/l, and .+-.0.381 mmol/l in case of 9 patterns, respectively. the signal processing using the neural network can reduce the errors ofthe electrolyte sensor outputs caused by the interference effect, thereby providing effectiveness in the improvement of the sensor selectivity.

• Journal of the Korean Society of Fashion and Beauty
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• v.6 no.1
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• pp.16-20
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• 2008

Ubiquitous computing which is called, the innovation of the 21st Century is a core technology of next generation. RFID technology is noticed, and physical distribution, home network, telematics, like industry automatization are developed by using various technique. Particulary, They use RFID technology for fashion and beauty industry, So, supplying network management, physical distribution management and warehouse management are investigated for the automatization. What we have investigated so far, a traceability system is made of ubiquitous sensor network for monitoring fashion and beauty industry environment. The proposed system using EPC network can provide information of industrial products traceability quickly and efficiently. Moreover, this system with RFID Technology gives intelligence of distribution and record. In this paper, We recommend the vision of Ubiquitous convergence of fashion and beauty industry.