• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.8
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• pp.667-677
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• 1990

In this paper, optical inplementation of the Hopfield neural network model for two-dimensinal associative memory is described For the real-time processing of two-dimensional images, the commercial LCTVs are used as a memory mask and an input spatical light modulator. A 4-D memory matrix is realized with a 2-D mask of a matrix arrangement and the inner-products between arbitrary input pattern and memory matrix are carried out by using the multifocus hololens. The output image is then electronically thresholded and fed back to the input of the associative memory system by 2-D CCd camera. From the good experimental results for the high error correction capability, the proposed system can be applied to practical pattern recognition and machine vision systems.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.17-27
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• 2005

In this study, it proposes the neural network system for character recognition and restoration. Proposes system composed by recognition part and restoration part. In the recognition part. it proposes model of effective pattern recognition to improve ART Neural Network's performance by restricting the unnecessary top-down frame generation and transition. Also the location feature extraction algorithm which applies with Hangeul's structural feature can apply the recognition. In the restoration part, it composes model of inputted image's restoration by Hopfield neural network. We make part experiments to check system's performance, respectively. As a result of experiment, we see improve of recognition rate and possibility of restoration.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.2
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• pp.183-191
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• 1991

This paper develops a pole-zero assignment self-tuning regulator utilizing the method of a neural network in the plant parameter estimation. An approach to parameter estimation of the plant with a Hopfield neural network model is proposed, and the control characteristics of the plant are evaluated by means of a simulation for a second-order linear time invariant plant. The results obtained with those of Exponentially Weighted Recursive Least Squares(EWRLS) method are also shown.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.6
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• pp.108-114
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• 1989

Introducing and optimizing bit-significance to the Hopfield model, ten highly correlated binary images, i.e., numbers "0" to "9", are successfully stored and retrieved in a $6{}8$ node system. Unlike many other neural network models, this model has stronger error correction capability for correlated images such as "6","8","3", and "9". The bit significance optimization is regarded as an adaptive learning process based on least-mean-square error algorithm, and may be implemented with Widrow-Hoff neural nets optimizer. A design for electro-optic implementation including the adaptive optimization networks is also introduced.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.1
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• pp.55-63
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• 1998

This paper presents a new maching algorithm by Hopfield Neural Network for 3-D object recognition. In the proposed method, a model object is represented by a set of polygons in a single coordinate. And each polygon is described by a set of features; feature attributes. In case of 3-D object recognition, the scale and poses of the object are important factors. So we propose a strategy for 3-D object recognition independently to its scale and poses. In this strategy, the respective features of the input or the model objects are changed to the startegical constants when they are compared with one another. Finally, we show that the proposed method has a robustness through the results of experiments which included the classification of the input objects and the matching sequence to its 3-D rotation and scale.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.221-223
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• 1993

The Hopfield model is defined as an adaptive dynamic system. In this paper we propose a modified neural network which is capable of solving linear programming problems and a set of linear equations. The model is directly implemented from the given system, and solves the problem without calculating the inverse of the matrices. We get the better stability results by the addition of scaling property and by using the nonlinearities in the linear programming neural networks.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.380-380
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• 2010

The chalcopyrite $ZnIn_2S_4$ epilayers were grown on the GaAs substrate by using a hot-wall epitaxy (HWE) method. The crystal field and the spin-orbit splitting energies for the valence band of the $ZnIn_2S_4$ have been estimated to be 0.1541 eV and 0.0129 eV, respectively, by means of the photocurrent spectra and the Hopfield quasicubic model. These results indicate that the splitting of the ${\Delta}so$ definitely exists in the $\Gamma_5$ states of the valence band of the $ZnIn_2S_4$/GaAs epilayer. The three photocurrent peaks observed at 10 K are ascribed to the $A_{1^-}$, $B_{1^-}$, and $C_1$-exciton peaks for n = 1. Also, we obtained the $A_{\infty^-}$ and B-exciton peaks from the PC spectrum at 293 K.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.12
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• pp.61-69
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• 1997

This paper proposes a new method for improving the performances of the neural network for optimization using a hyubrid of gradient descent method and dynamic tunneling system. The update rule of gradient descent method, which has the fast convergence characteristic, is applied for high-speed optimization. The update rule of dynamic tunneling system, which is the deterministic method with a tunneling phenomenon, is applied for global optimization. Having converged to the for escaping the local minima by applying the dynamic tunneling system. The proposed method has been applied to the travelling salesman problems and the optimal task partition problems to evaluate to that of hopfield model using the update rule of gradient descent method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.233-242
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• 2019

ZHD (Zenith Hydrostatic Delay) model is important parameter in estimating of GNSS (Global Navigation Satellite System) PWV (Precipitable Water Vapor) along with weighted mean temperature. The ZWD (Zenith Wet Delay) is tend to accumulate the ZHD error, so that biases from ZHD will be affected on the precision of GNSS PWV. In this paper, we compared the accuracy of GNSS PWV with radiosonde PWV using three ZHD models, such as Saastamoinen, Hopfield, and Black. Also, we adopted the KWMT (Korean Weighted Mean Temperature) model and the mean temperature which was observed by radiosonde on the retrieval processing of GNSS PWV. To this end, GNSS observation data during one year were processed to produce PWVs from a total of 5 GNSS permanent stations in Korea, and the GNSS PWVs were compared with radiosonde PWVs for the evaluating of biases. The PWV biases using mean temperature estimated by the KWMT model are smaller than radiosonde mean temperature. Also, we could confirm the result that the Saastamoinen ZHD which is most used in the GNSS meteorology is not valid in South Korea, because it cannot be exclude the possibility of biases by latitude or height of GNSS station.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.232-235
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• 1999

This paper presents a HNN(Hopfield Neural Network) model to solve the ORP(Optimal Routing Problem) in DSP(Distribution System Planning). This problem is generally formulated as a combinatorial optimization problem with various equality and inequality constraints. Precedent study[3] considered only fixed cert, but in this paper, we proposed the capability of optimization by fixed cost and variable cost. And suggested the corrected formulation of energy function for improving the characteristics of convergence. The proposed algorithm has been evaluated through the sample distribution planning problem and the simmulation results are presented.