• Title/Summary/Keyword: sigmoid

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Prediction of plasma etching using genetic-algorithm controlled backpropagation neural network

  • Kim, Sung-Mo;Kim, Byung-Whan
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1305-1308
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    • 2003
  • A new technique is presented to construct a predictive model of plasma etch process. This was accomplished by combining a backpropagation neural network (BPNN) and a genetic algorithm (GA). The predictive model constructed in this way is referred to as a GA-BPNN. The GA played a role of controlling training factors simultaneously. The training factors to be optimized are the hidden neuron, training tolerance, initial weight magnitude, and two gradients of bipolar sigmoid and linear functions. Each etch response was optimized separately. The proposed scheme was evaluated with a set of experimental plasma etch data. The etch process was characterized by a $2^3$ full factorial experiment. The etch responses modeled are aluminum (A1) etch rate, silica profile angle, A1 selectivity, and dc bias. Additional test data were prepared to evaluate model appropriateness. The GA-BPNN was compared to a conventional BPNN. Compared to the BPNN, the GA-BPNN demonstrated an improvement of more than 20% for all etch responses. The improvement was significant in the case of A1 etch rate.

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Design of a Digital Neuron Processor Using the Residue Number System (잉여수 체계를 이용한 디지털 뉴론 프로세서의 설계)

  • 윤현식;조원경
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.10
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    • pp.69-76
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    • 1993
  • In this paper we propose a design of a digital neuron processor using the residue number system for efficient matrix.vector multiplication involved in neural processing. Since the residue number system needs no carry propagation for modulus operations, the neuron processor can perform multiplication considerably fast. We also propose a high speed algorithm for computing the sigmoid function using the specially designed look-up table. Our method can be implemented area-effectively using the current technology of digital VLSI and siumlation results positively demonstrate the feasibility of our method. The proposed method would expected to adopt for application field of digital neural network, because it could be realized to currently developed digital VLSI Technology.

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A Neural Network Based on Stochastic Computation using the Ratio of the Number of Ones and Zeros in the Pulse Stream (펄스열에서 1인 펄스수와 0인 펄스수의 비를 이용하여 확률연산을 하는 신경회로망)

  • 민승재;채수익
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.7
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    • pp.211-218
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    • 1994
  • Stochastic computation employs random pulse streams to represent numbers. In this paper, we study a new method to implement the number system which uses the ratio of the numbers of ones and zeros in the pulse streams. In this number system. if P is the probability that a pulse is one in a pulse stream then the number X represented by the pulse stream is defined as P/(1-P). We propose circuits to implement the basic operations such as addition multiplication and sigmoid function with this number system and examine the error characteristics of such operations in stochastic computation. We also propose a neuron model and derive a learning algorithm based on backpropagation for the 3-layered feedforward neural networks. We apply this learning algorithm to a digit recognition problem. To analyze the results, we discuss the errors due to the variance of the random pulse streams and the quantization noise of finite length register.

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Synthesis of 3-D spatial matched filter for real-time 3-D image display (실시간 입체 영상 디스플레이를 위한 3차원 공간정합 필터의 합성)

  • 임선호;김은수
    • Journal of the Korean Institute of Telematics and Electronics D
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    • v.34D no.8
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    • pp.62-70
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    • 1997
  • In this paper, we presetn a new method to display 3-D image modelled as a sum of 2-D sliced images by expanding the concept of the conventional 2-D optical correlator based on spatial matched filtr to the 3-D region. It is hsown that a arbitrary image can be constructed by an array of the correlation-peaks between pixel-to-pixel and propose the systhesis precedure of 3-D spatial-matched-fjilter using fresnel diffraction equation to display 3-D image in space. It is also shown that the quantization problem is severe when the systehsised filter function is displayed on the conventional LC-SLM. To overcome this problem, anonlinear quantizaton method using the sigmoid function is suggested, and this method can reduce the bias and the loss of high spatial-frequency information, and improve the diffraction efficiency. Finally, the suggested method is tested by computer simulation and then approved by some optical experiments with the conventional LC-SLM.

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Analysis of flow through dam foundation by FEM and ANN models Case study: Shahid Abbaspour Dam

  • Shahrbanouzadeh, Mehrdad;Barani, Gholam Abbas;Shojaee, Saeed
    • Geomechanics and Engineering
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    • v.9 no.4
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    • pp.465-481
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    • 2015
  • Three-dimensional simulation of flow through dam foundation is performed using finite element (Seep3D model) and artificial neural network (ANN) models. The governing and discretized equation for seepage is obtained using the Galerkin method in heterogeneous and anisotropic porous media. The ANN is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning, using the water level elevations of the upstream and downstream of the dam, as input variables and the piezometric heads as the target outputs. The obtained results are compared with the piezometric data of Shahid Abbaspour's Dam. Both calculated data show a good agreement with available measurements that demonstrate the effectiveness and accuracy of purposed methods.

On The Application of Hopfield Neural Network to Economic Load Dispatching of Electric Power (흡필드 신경회로망에 의한 전력경제급전)

  • Eom, Il-Kyu;Kim, Yoo-Shin;Park, June-Ho
    • Proceedings of the KIEE Conference
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    • 1990.11a
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    • pp.247-251
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    • 1990
  • Hopfield neural network has been applied to the problem of economic load dispatching of electric power(ELD). The optimum values of neuron potentials are represented in terms of large numbers. And the neuron potential converges to the medium values between the limit values of the sigmoid function. In three cases, ELD based upon Hopfield network is formulated, solved and discussed.

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Recognition of hand written Hangul by neural network

  • Song, Jeong-Young;Lee, Hee-Hyol;Choi, Won-Kyu;Akizuki, Kageo
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.76-80
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    • 1993
  • In this paper we discuss optimization of neural network parameters, such as inclination of the sigmoid function, the numbers of the input layer's units and the hidden layer's units, considering application to recognition of hand written Hangul. Hangul characters are composed of vowels and consonants, and basically classified to six patterns by their positions. Using these characteristics of Hangul, the pattern of a given character is determined by its peripheral distribution and the other features. After then, the vowels and the consonants are recognized by the optimized neural network. The constructed recognition system including a neural network is applied to non-learning Hangul written by some Korean people, which are the names randomly taken from Korean spiritual and cultural research institute.

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Learning of multi-layer perceptrons with 8-bit data precision (8비트 데이타 정밀도를 가지는 다층퍼셉트론의 역전파 학습 알고리즘)

  • 오상훈;송윤선
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.4
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    • pp.209-216
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    • 1996
  • In this paper, we propose a learning method of multi-layer perceptrons (MLPs) with 8-bit data precision. The suggested method uses the cross-entropy cost function to remove the slope term of error signal in output layer. To decrease the possibility of overflows, we use 16-bit weighted sum results into the 8-bit data with appropriate range. In the forwared propagation, the range for bit-conversion is determined using the saturation property of sigmoid function. In the backwared propagation, the range for bit-conversion is derived using the probability density function of back-propagated signal. In a simulation study to classify hadwritten digits in the CEDAR database, our method shows similar generalization performance to the error back-propagation learning with 16-bit precision.

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A Design of Artificial Emotion Model (인공 감정 모델의 설계)

  • Lee, In-Geun;Seo, Seok-Tae;Jeong, Hye-Cheon;Gwon, Sun-Hak
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.04a
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    • pp.58-62
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    • 2007
  • 인간이 생성한 음성, 표정 영상, 문장 등으로부터 인간의 감정 상태를 인식하는 연구와 함께, 인간의 감정을 모방하여 다양한 외부 자극으로 감정을 생성하는 인공 감정(Artificial Emotion)에 관한 연구가 이루어지고 있다. 그러나 기존의 인공 감정 연구는 외부 감정 자극에 대한 감정 변화 상태를 선형적, 지수적으로 변화시킴으로써 감정 상태가 급격하게 변하는 형태를 보인다. 본 논문에서는 외부 감정 자극의 강도와 빈도뿐만 아니라 자극의 반복 주기를 감정 상태에 반영하고, 시간에 따른 감정의 변화를 Sigmoid 곡선 형태로 표현하는 감정 생성 모델을 제안한다. 그리고 기존의 감정 자극에 대한 회상(recollection)을 통해 외부 감정 자극이 없는 상황에서도 감정을 생성할 수 있는 인공 감정 시스템을 제안한다.

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Hirschsprung's Disease Associated with Neonatal Intestinal Perforation (장 천공을 동반한 Hirschsprung씨 병 3예 보고)

  • Kim, Seong-Chul;Sea, Byong-Sun;Liu, Shan King;Kim, In-Koo
    • Advances in pediatric surgery
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    • v.1 no.2
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    • pp.186-189
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    • 1995
  • Neonatal intestinal perforation is mainly caused by necrotizing enterocolitis, intestinal atresia, meconium ileus or unknown etiology. Occasionally, Hirschsprung's disease presents with neonatal intestinal perforation, of which, it is known that total colonic aganglionosis is common. Therefore, Hirschsprung's disease should be considered as a cause of neonatal intestinal perforation. The authors have experienced 3 cases of neonatal Hirschsprung's disease associated with colonic perforations. Cecal perforations were noted in 2 cases with aganglionosis from descending colon and sigmoid perforation in a case with aganglionosis in rectum. These cases will be discussed with literature review.

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