• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1996.10a
• /
• pp.257-260
• /
• 1996

This study is about the construction of algorithm for selecting Yongshin of the Four Pillars. To emulate the method the expert uses when he select the Yongshin, we introduce the Hopfield Network. The result of the simulation classified with Yongshin is presented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.05a
• /
• pp.87-91
• /
• 2001

This paper discusses the influence of input conductance on the convergece of the continuous Hopfield neural networks. The convergence has been analyzed for the input and output nodes of neurons. Also, the characteristics of equilibrium points has been analyzed depending on different values of the input conductance.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.45 no.6
• /
• pp.16-21
• /
• 2008

This paper introduces a new type of Hopfield neural network using newly developed single-electron devices. In the electrical model of the Hopfield neural network, a single-electron synapse, used as a voltage(or current)-variable resistor, and two stages of single-electron inverters, used as a nonlinear activation function, are simulated with a single-electron circuit simulator using Monte-Carlo method to verily their operation.

• Journal of IKEEE
• /
• v.4 no.2 s.7
• /
• pp.192-201
• /
• 2000

This paper discusses the influence of the input conductance on system stability for the continuous type Hopfield Neural Networks.. The input conductance is connected from the neuron input to ground. The input conductance has been proved to effect on stability in input space. Transient analysis is used to test the stability in input space. Also, it has been studied how to adjust the input conductance for improving the system's performance.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.5
• /
• pp.877-883
• /
• 2001

In this paper, we propose a new Genetic Algorithm(GA)-based Multiuser Detector(MUD), and its performance is evaluated by computer simulation compared to both the optimum MUD and the Hopfield neural network(NN) -based MUD when the near-far problem exists. From the results of comprehensive simulation, it is shown that the proposed MUD in this paper can guarantee a close BER performance compared to both the optimum MUD and the Hopfield NN MUD with a considerable reduced complexity under the near-far condition. Furthermore, a more performance improvement than the Hopfield W MUD can be expected when the near-far problem does not exist.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.01a
• /
• pp.43-44
• /
• 2019

본 논문에서는 머신러닝 알고리즘 중 하나인 Hopfield Network 알고리즘을 이용하여 SDN 환경에서 분산된 컨트롤러를 선택하는 모델을 제안하였다. Hopfield Network 알고리즘은 신경망의 물리적 모델로써 최적화, 연상기억 등에 사용되는데 이를 통해 효율적인 컨트롤러 동기화를 기대한다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.6A
• /
• pp.379-385
• /
• 2003

In this paper, we propose a time constant control method for sieving local minimum problem of the multiuser detector using Hopfield neural network for synchronous multi-rate code division multiple access(CDMA) system in selective fading environments and its performance is compared with that of the parallel interference cancellation(PIC). We also assume that short scrambling codes of 256 chip length are used an uplink, suggest a simple correlation estimation algorithm and circuit complexity reduction method by using cyclostationarity property of short scrambling code.It is verified that multiuser detector using Hopfield neural network more efficiently cancels multiple access interference(MAI) and obtain better bit error rate and near-far resistant than conventional detector.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.3
• /
• pp.339-347
• /
• 1993

The channel assignment problem in a mobile communication system is a NP-complete combinatorial optimization problem, in which the calculation time increases exponentially as the range of the problem is extended. This paper adapts a conventional Hopfield neural network model to the channel assignment problem to relieve the calculation time by means of the parallelism supplied from the neural network. In the simulation study, we checked the feasability of such a parallel method for the fixed channel assignment with uniform, and nouniform channel requirements, and for the dynamic channel assignment with considering continously varying channel requirements.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1774-1777
• /
• 1997

As factory automation is required, using the vision system is also essential. Especially, the pateh planning of parts with J-lead on PCB plays a import role of whole automation. Path planning is required because J-lead is scatteed compaed to L-lead on PCB. Therefore, in this paper, we propose path planning of part inspection with J-lead to use Hopfield Model(TSP : Traveling Salesman Problem). Then optical system suited to J-lead inspection is designed and the algorithm of J-lead solder joint and part inspection is proposed.

• Journal of applied mathematics & informatics
• /
• v.31 no.3_4
• /
• pp.577-594
• /
• 2013

In this paper, we study the global stability and the existence of almost periodic solution of high-order Hopfield neural networks with distributed delays of neutral type. Some sufficient conditions are obtained for the existence, uniqueness and global exponential stability of almost periodic solution by employing fixed point theorem and differential inequality techniques. An example is given to show the effectiveness of the proposed method and results.