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Neural nets for adaptive filtering and adaptive pattern recognition

B. Widrow, R. Winter
1988 Computer  
Today neural nets are the focus of widespread research interest. Areas of investigation include pattern recognition and trainable logic.  ...  This article describes practical applications of the ALC in signal processing and pattern recognition.  ...  Adaptive pattern recognition The adaptive threshold element of Figure 3 can be used for pattern recognition and as a trainable logic device.  ... 
doi:10.1109/2.29 fatcat:k3cuq5qzerf5hlg22uowfsyfae

Adaptive and Intelligent Systems for Generator Monitoring and Protection Purposes

Waldemar Rebizant, Janusz Szafran, Seung-Jae Lee, Sang-Hee Kang
2003 IFAC Proceedings Volumes  
New adaptive scheme for signal parameter measurement for generator monitoring and protection is presented.  ...  The filter data window length and coefficients are adapted according to coarsely estimated signal frequency.  ...  The results given below were obtained for a population of 20 nets trained with a half of available short-circuit patterns and tested with all patterns. Fifty generations of nets were assumed.  ... 
doi:10.1016/s1474-6670(17)34473-7 fatcat:szhfjntqffajniwejv75iyycqm

Page 2158 of Psychological Abstracts Vol. 77, Issue 9 [page]

1990 Psychological Abstracts  
(Boston U, Ctr for Adaptive Sys- tems, MA) Neural network models for pattern recognition and associative memory. Neural Networks, 1989, Vol 2(4), 243-257.  ...  —Outlines some fundamental neural network modules for associ- ative memory, pattern recognition, and category learning.  ... 

Automated Textile Defect Recognition System Using Computer Vision And Artificial Neural Networks

Atiqul Islam, Shamim Akhter, Tumnun E. Mursalin
2008 Zenodo  
In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration  ...  The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time.  ...  The second part of the paper uses the input set to recognize the defects and adapts the neural net. A.  ... 
doi:10.5281/zenodo.1080145 fatcat:o6xay4iid5ddzimsvn3ld5gcdu

Neural Computing, an Introduction

1993 Discrete Applied Mathematics  
Early Vision, Focal Attention, and Neural Nets (Bela Julesz). Towards Hierarchical Matched Filtering (Robert Hecht-Nielsen). Some Variations on Training of Recurrent Networks (Gary  ...  Humans and computers. The structure of the brain. Learning in machines. The differences. Chapter 2: Pattern Recognition. Introduction. Pattern recognition in perspective.  ... 
doi:10.1016/0166-218x(93)90142-b fatcat:p4ste5qwqbepnhpkepump54dju

Page 4905 of Psychological Abstracts Vol. 82, Issue 10 [page]

1995 Psychological Abstracts  
networks; layered neural nets; LMS or Widrow-Hoff Delta Rule for the single neuron, adaptation of layered neural nets by the MRII Rule; application of layered networks to pattern recognition; invariance  ...  Neural nets for and adaptive pattern . [In: (PA Vol 82:39236) An introduction to neural and electronic networks (2nd ed.). Neural networks: Foundations to applications.  ... 

Japanese digits recognition by neural networks using vocal tract shapes

Hiroshi Kinugasa, Hiroyuki Kamata, Yoshihisa Ishida
1993 Journal of the Acoustical Society of Japan (E)  
This paper presents a new system for spoken Japanese digits recognition by a neural network using vocal tract shapes. The vocal tract shape is a suitable parameter for synthesis or recognition.  ...  Finally, we show the recognition results to prove the effectiveness of our method, and we show that the CG algorithm has several advantages compared to the BP algorithm.  ...  Ogawa of Meiji University and Prof. C. Charalambous of Kuwait University for their helpful advices.  ... 
doi:10.1250/ast.14.55 fatcat:rduxn6hwvranjfg2segrimfrpi

Plate Number Recognition Using Segmented Method with Artificial Neural Network

Auwal Salisu Yunusa, A. R. Dansharif, M. Bello, H. Abdullahi, S. A. Muhammad, S. I. Abdullahi
2022 Zenodo  
The second one is the use of the neural network; three different types of networks were used. (Pattern net, perceptron, and multi-layer neural network).  ...  This article presents a license plate number recognition system for moving vehicles for Turkish license plates.  ...  For pattern net and MLP, four different types of architectures of the neural network are used to observe the performances of the network.  ... 
doi:10.5281/zenodo.6564338 fatcat:mujvtm46hrazzdlvxhxrzyie4u

NNGD algorithm for neural adaptive filters

D.P. Mandic
2000 Electronics Letters  
of Q, for a contractive activation function (p < 4) the following learning rate for a normalised GD based algorithm for a neural adaptive fdter can be adopted: where net@) = xT(k)w(k), and C is a constant  ...  ., 1992 , IP-1, pp. 205-220 IP-7, pp. 1547 -1560 NNGD algorithm for neural adaptive filters D.P.  ... 
doi:10.1049/el:20000631 fatcat:cc7plltjmreqdgqio7hhf6dtcy

Layered neural nets for pattern recognition

B. Widrow, R.G. Winter, R.A. Baxter
1988 IEEE Transactions on Acoustics Speech and Signal Processing  
The entire recognition system is a layered network of ADALINE neurons. The ability to adapt a multilayered neural net is fundamental.  ...  A pattern recognition concept involving first an "invariance net" and second a "trainable classifier" is proposed.  ...  neural nets, and would be a useful practical product.  ... 
doi:10.1109/29.1638 fatcat:sfhdk46q75epdb7yfmuxeiscaq

Page 1221 of Neural Computation Vol. 6, Issue 6 [page]

1994 Neural Computation  
Probabilistic interpretation of feedforward classification net- work outputs, with relation to statistical pattern recognition. In Neuro- Computing: Algorithms, Architectures and Applications, F.  ...  Introduction To Adaptive Filters. Macmillan, New York. Jacobs, R., Jordan, M., Nowlan, S., and Hinton, G. 1991. Adaptive mixtures of local experts. Neural Comp. 3(1), 79-87.  ... 

Posture Recognition and Imitation using Haar Wavelet Transform and Neural Networks

J. Yaser Daanial Khan, M. Khalid Mahmood
2018 Journal of Intelligent Computing  
A database containing nearly 2000 images was created for this purpose. Furthermore a neural network for the purpose of pattern recognition among segmented images was trained.  ...  Our research and implementation revolves around the use of an ordinary inexpensive camera to acquire live video and hence segment the human forearm locations using various filters.  ...  Live Neural Net Testing The feature vector is thenclamped to the neural net for testing. This classifies the image to one of the 49 classes of postures.  ... 
doi:10.6025/jic/2018/9/4/133-143 fatcat:dx2o3nfa65e55jwpiuq2b6rbty

Speech Recognition with Missing Data using Recurrent Neural Nets

Shahla Parveen, Phil D. Green
2001 Neural Information Processing Systems  
In this paper we develop a connectionist approach to the problem of adapting speech recognition to the missing data case, using Recurrent Neural Networks.  ...  In contrast to methods based on Hidden Markov Models, RNNs allow us to make use of long-term time constraints and to make the problems of classification with incomplete data and imputing missing values  ...  Acknowledgement This work is being supported by Nokia Mobile Phones, Denmark and the UK Overseas Research Studentship scheme.  ... 
dblp:conf/nips/ParveenG01 fatcat:fzosbveuw5ezpfp4fstdxvl6v4

Neural network models for pattern recognition and associative memory

Gail A Carpenter
1989 Neural Networks  
learning, and pattern recognition.  ...  and size-invariant pattern recognition.  ... 
doi:10.1016/0893-6080(89)90035-x fatcat:yyu736xvrrdktdofya5pu5fxxm

The Use of Neural Network to Recognize the Parts of the Computer Motherboard

Abbas M. Ali, S.D. Gore, Musaab AL-Sariera
2005 Journal of Computer Science  
The main thrust is to identify different parts of the motherboard using a Hopfield Neural Network. The outcome of the net is compared with the objects stored in the database.  ...  The proposed scheme is implemented using bottom -up approach, where steps like edge detection, spatial filtering, image masking..etc are performed in sequence. the scheme is simulated in MATLAB environment  ...  biological Neural Networks [1] Neural Networks have became a popular technique for pattern recognition, face detection [1, [3] [4] [5] .  ... 
doi:10.3844/jcssp.2005.477.481 fatcat:a342yx5e5rg7xcxb3i5t7lahii
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