The hidden layer design of the MVQ neural network

被引:0
|
作者
Abouali, AH [1 ]
Porter, WA [1 ]
机构
[1] Egyptian Res Ctr, Cairo 11435, Egypt
关键词
D O I
10.1109/SSST.1998.660103
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this study, we introduce the first part of neural network classifiers design methodology. The design has a lot of the desired features. The design is based on a preprocessing stage of multiple class vector quantization, MVQ, algorithm. The algorithm extracts the information from the training set. The outcome of this stage fully defines the first hidden layer of the network. The methodology not only has better performance but also provides insights to why and how the neural network works.
引用
下载
收藏
页码:393 / 396
页数:4
相关论文
共 50 条
  • [21] Factorized Hidden Layer Adaptation for Deep Neural Network Based Acoustic Modeling
    Samarakoon, Lahiru
    Sim, Khe Chai
    IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2016, 24 (12) : 2241 - 2250
  • [22] Wind energy prediction using a two-hidden layer neural network
    Grassi, Giuseppe
    Vecchio, Pietro
    COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2010, 15 (09) : 2262 - 2266
  • [23] Spurious valleys in one-hidden-layer neural network optimization landscapes
    Venturi, Luca
    Bandeira, Afonso S.
    Bruna, Joan
    Journal of Machine Learning Research, 2019, 20
  • [24] Simultaneous Approximation Algorithm Using a Feedforward Neural Network with a Single Hidden Layer
    Hahm, Nahmwoo
    Hong, Bum Il
    JOURNAL OF THE KOREAN PHYSICAL SOCIETY, 2009, 54 (06) : 2219 - 2224
  • [25] Layered neural network training with model switching and hidden layer feature regularization
    Kameyama, K
    Taga, K
    PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS 2003, VOLS 1-4, 2003, : 2294 - 2299
  • [26] Extending hidden-layer backpropagation neural network and its' training algorithm
    School of Computer and Communication Engineering, China University of Petroleum, Dongying 257061, China
    不详
    Jisuanji Jicheng Zhizao Xitong, 2008, 11 (2284-2288):
  • [27] Binary Neural Network Classifier and it's Bound for the Number of Hidden Layer Neurons
    Chaudhari, Narendra S.
    Tiwari, Aruna
    11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV 2010), 2010, : 2012 - 2017
  • [28] Nuclear mass predictions with multi-hidden-layer feedforward neural network
    Le, Xian-Kai
    Wang, Nan
    Jiang, Xiang
    NUCLEAR PHYSICS A, 2023, 1038
  • [29] Spurious Valleys in One-hidden-layer Neural Network Optimization Landscapes
    Venturi, Luca
    Bandeira, Afonso S.
    Bruna, Joan
    JOURNAL OF MACHINE LEARNING RESEARCH, 2019, 20
  • [30] A new deep neural network based on a stack of single-hidden-layer feedforward neural networks with randomly fixed hidden neurons
    Hu, Junying
    Zhang, Jiangshe
    Zhang, Chunxia
    Wang, Juan
    NEUROCOMPUTING, 2016, 171 : 63 - 72