• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.7
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• pp.70-78
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• 1992

In this paper, an approach for 3-D object segmentation and classification, which is based on eigen-values of polynomial function as their surface features, using neural network is proposed. The range images of 3-D objects are classified into surface primitives which are homogeneous in their intrinsic eigenvalue properties. The misclassified regions due to noise effect are merged into correct regions satisfying homogeneous constraints of Hopfield neural network. The proposed method has advantage of processing both segmentation and classification simultaneously.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.397-400
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• 1989

This study is to design a method of parameter estimation for a second order linear time invarient system of self-tuning controller utilizing the neural network theory proposed by Hopfield. The result is compared with the other methods which are commonly used in controller theories.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.124-126
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• 1989

Inverse kinematic problem is a crucial point for robot manipulator control. In this paper, to implement the Jacobian control technique we used the Hopfield(Tank)'s neural network. The states of neurons represent joint veocities, and the connection weights are determined from the current value of the Jacobian matrix. The network energy function is constructed so that its minimum corresponds to the minimum least square error. At each sampling time, connection weights and neuron states are updated according to current joint position. Inverse kinematic solution to the planar redundant manipulator is solved by computer simulation.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.5
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• pp.59-68
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• 1998

This paper proposes a neural network algorithm for a channel assignment in cellular mobile communications. The proposed algorithm is developed base on hopfield neural network in order to minimize the number of channel without a confliction between cells. To compare the performance of the proposed algorithm, we used seven benchmark problems selected from kunz's and funabiki's papers. Experimental results show that the convergence times are reduced form 27% to 66% compared with Kunz's and funabiki's algorithm and vonvergence rates are improved to 100%.

• 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 Korea Society of Computer and Information
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• v.4 no.4
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• pp.94-100
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• 1999

This paper concerns the implementation of a digital neural network which performs the high speed operation of Hopfield model's arithmetic operation. It is also designed to use a look-up table and produce floating point arithmetic of nonlinear function with high speed operation. The arithmetic processing of Hopfleld is able to describe the matrix-vector operation, which is adaptable to design the array processor because of its recursive and iterative operation .The proposed method is expected to be applied to the field of real neural networks because of the realization of the current VLSI techniques.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.319-322
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• 2002

In this paper, we present a digital authentication technique using content-based watermarking in digital images. To digest the image contents, Hopfield network is employed on the block-based edge image. The Hopfield function extracts the same tit fur similarly looking blocks so that the values are unlikely to change to the innocuous manipulations while being changed far malicious manipulations. By inputting the extracted bit sequence with secret key to the cryptographic hash function, we generate a watermark for each block by seeding a pseudo random number generator with a hash output Therefore, the proposed authentication technique can distinguish between malicious attacks and innocuous attacks. Watermark embedding is based on the block-based spread spectrum method in DCT domain and the strength of watermark is adjusted according to the local statistics of DCT coefficients in a zig-zag scan line in AC subband. The numerical experiments show that the proposed technique is very efficient in the performance of robust authentication.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.591-594
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• 2003

본 논문에서는 hopfield 신경망을 사용한 다양한 부분적인 패턴 복원에 관하여 연구하였다. 여섯 개의 $32{\times}32$ 비트맵 훈련패턴들은 한글자음 ㄱ, ㅁ, ㅂ, ㅇ, ㅊ, ㅍ, 그리고 남자와 여자 이미지로 구성되어 있다. 그리고 부분패턴들의 크기, 범위, 방향의 효과를 알아보기 위해서 훈련패턴에서 여덟 가지 형태의 테스트 패턴을 만든다. 한글 자음의 경우 유사 패턴이 많기 때문에 완전히 복원되지 못하였으나, 400회 정도 수렵된 후에는 테스트패턴들이 견본패턴과 비슷한 모양으로 복원되었다. 이 유사도를 측정하기 위해 해밍거리 (Hamming distance)를 이용하였다. 유사도를 측정하여 해밍거리가 가장 적은 것으로 본래의 이미지들 복원하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.559-565
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• 2013

Spatial resolution of land covers from remotely sensed images can be increased using super-resolution mapping techniques for soft-classified land cover proportions. A further development of super-resolution mapping technique is downscaling the original remotely sensed image using super-resolution mapping techniques with a forward model. In this paper, the model for increasing spatial resolution of remote sensing multispectral image is tested with real SPOT 5 imagery at 10m spatial resolution for an area in Bac Giang Province, Vietnam in order to evaluate the feasibility of application of this model to the real imagery. The soft-classified land cover proportions obtained using a fuzzy c-means classification are then used as input data for a Hopfield neural network (HNN) to predict the multispectral images at sub-pixel spatial resolution. The 10m SPOT multispectral image was improved to 5m, 3,3m and 2.5m and compared with SPOT Panchromatic image at 2.5m resolution for assessment.Visually, the resulted image is compared with a SPOT 5 panchromatic image acquired at the same time with the multispectral data. The predicted image is apparently sharper than the original coarse spatial resolution image.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.10
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• pp.66-74
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• 1999

In this paper, we propose a generalized model of statistical Hopfield neural network applicable to solving the well known NP-Complete problem, TSP. Van Den Bout's method to simplify the energy function through normalization has severe weak points that it does not consider the necessary perturbation effects. In proposed model, the improved energy function is used and 5 kinds of perturbation effects and the ratio between perturbation effects are considered including van Den Bout's 2 kinds and one more kind of Park. Through the simulation of randomly generated distribution of 10-city, it is found that our model shows 90 out of 100 cases reach the optimum and near optimum solution(within 5% error). We show the simulation of the large scale, 30-city and 50-city.