Neural Processing Letters, Volume 19

Volume 19, Number 1, 2004

• Min-Ling Zhang, Zhi-Hua Zhou:
  Improve Multi-Instance Neural Networks through Feature Selection. 1-10
  
• Pablo A. Estévez, Yoichi Okabe:
  On the Computational Power of Max-Min Propagation Neural Networks. 11-23
  
• Sergio Bermejo, Joan Cabestany:
  Ensemble Learning for Chemical Sensor Arrays. 25-35
  
• Raffaele Calabretta, Andrea Di Ferdinando, Domenico Parisi:
  Ecological Neural Networks for Object Recognition and Generalization. 37-48
  
• Ting Qin, Zonghai Chen, Haitao Zhang, Sifu Li, Wei Xiang, Ming Li:
  A Learning Algorithm of CMAC Based on RLS. 49-61
  
• Koji Tsuda, Shinsuke Uda, Taishin Kin, Kiyoshi Asai:
  Minimizing the Cross Validation Error to Mix Kernel Matrices of Heterogeneous Biological Data. 63-72
  
• Hongjian Liu, Hongya Tuo, Yuncai Liu:
  Rough Neural Network of Variable Precision. 73-87
  

Volume 19, Number 2, 2004

• Huilin Ye, Hanchang Liu:
  A Fuzzy-Related Thesaurus for Query Refinement. 97-107
  
• Jean-François Kamp, Franck Poirier, Philippe Doignon:
  Interaction with In-Vehicle Electronic Systems: A Complete Description of a Neural Network Approach. 109-129
  
• Changyin Sun, Chun-Bo Feng:
  Exponential Periodicity of Continuous-time and Discrete-Time Neural Networks with Delays. 131-146
  
• Richard Walker, Vincenzo Russo:
  Memory Consolidation and Forgetting During Sleep: A Neural Network. 147-156
  
• Nikolaos Ampazis, Stavros J. Perantonis:
  LSISOM - A Latent Semantic Indexing Approach to Self-Organizing Maps of Document Collections. 157-173
  

Volume 19, Number 3, June 2004

• Armando M. Fernandes, Andrei B. Utkin, Alexander V. Lavrov, Rui M. Vilar:
  Neural Network Based Recognition of Smoke Signatures from Lidar Signals. 175-189
  
• Sunghwan Sohn, Cihan H. Dagli:
  Ensemble of Evolving Neural Networks in Classification. 191-203
  
• Mehmet Kerem Müezzinoglu, Cüneyt Güzelis:
  Associative Memory Design via Path Embedding into a Graph. 205-209
  
• Chenn-Jung Huang, Wei-Chen Liao:
  Application of Probabilistic Neural Networks to the Class Prediction of Leukemia and Embryonal Tumor of Central Nervous System. 211-226
  
• Richard K. K. Yuen, Eric W. M. Lee, Chee Peng Lim, Grace W. Y. Cheng:
  Fusion of GRNN and FA for Online Noisy Data Regression. 227-241
  

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