Triennial report 1997-1999

Preface

Personnel

1 The Self-Organizing Map (SOM)
   Teuvo Kohonen

2 Analyzing Self-Organization in the SOM
   Adrian Flanagan

3 Point Density of the Model Vectors in the SOM
   Teuvo Kohonen

4 The SOM as a Model of Brain Maps
   Teuvo Kohonen

5 Speedup of SOM Computation
   Teuvo Kohonen

6 Fast Evolutionary Learning in the SOM
   Teuvo Kohonen

7 Clustering and Visualization of Large Protein Sequence Databases by Means of an Extension of the Self-Organizing Map
   Panu Somervuo and Teuvo Kohonen

8 Exploratory Data Analysis and Data Mining Using the Self-Organizing Map
   Samuel Kaski and Teuvo Kohonen

9 New Methods for Interpreting Self-Organizing Maps in Data Analysis
   Samuel Kaski, Janne Nikkilä, and Teuvo Kohonen

10 Coloring that Reveals Cluster Structures in High-Dimensional Data
   Samuel Kaski, Jarkko Venna, and Teuvo Kohonen

11 Self-Organization of Very Large Document Collections
   Teuvo Kohonen, Samuel Kaski, Krista Lagus, Timo Honkela, Jarkko Salojärvi, Jukka Honkela, Vesa Paatero, Antti Saarela, and Antti Ahonen

12 Construction of Random Projections of Word Histograms by Pointers
   Teuvo Kohonen

13 Method for Characterizing Document Map Areas with Keywords
   Krista Lagus and Samuel Kaski

14 Speech Recognition
   Mikko Kurimo and Panu Somervuo

15 Using SOM and LVQ for HMM Training
   Mikko Kurimo

16 Time Topology for the Self-Organizing Map
   Panu Somervuo

17 The Self-Organizing Map and Learning Vector Quantization for Feature Sequences
   Panu Somervuo and Teuvo Kohonen

18 Redundant Hash Addressing of Feature Sequences using the Self-Organizing Map
   Panu Somervuo

19 Unsupervised Neural Learning for Independent Component Analysis and Blind Source Separation
   Erkki Oja, Juha Karhunen, Aapo Hyvärinen, Petteri Pajunen, Ricardo Vigário, and graduate students

20 Nonlinear PCA Learning Rules forIndependent Component Analysis and Blind Source Separation
   Juha Karhunen, Erkki Oja, and Petteri Pajunen

21 Extensions of the Basic Source Separation Problem
   Petteri Pajunen, Juha Karhunen, Aapo Hyvärinen, and Simona Mâlâroiu

22 The FastICA Algorithm
   Aapo Hyvärinen, Erkki Oja, Ella Bingham, and Râzvan Cristescu

23 Natural Image Statistics and Independent Component Analysis
   Aapo Hyvärinen, Patrik O.\ Hoyer and Erkki Oja

24 Analysis of Independent Components in EEG and MEG
   Ricardo Vigário, Jaakko Särelä, and Erkki Oja

25 Bayesian Learning for Generative Models and Independent Component Analysis
   Harri Lappalainen, Xavier Giannakopoulos, Antti Honkela, and Juha Karhunen

26 Intelligent Process Data Analysis
   Olli Simula, Jussi Ahola, Esa Alhoniemi, Johan Himberg, Pekka Hippeläinen, Jaakko Hollmén, Juha Parhankangas, Jukka Parviainen, Juha Vesanto, and Henry Stenberg

27 Adaptive Receivers Based on Self-Organizing Maps
   Kimmo Raivio and Olli Simula

28 Adaptive Resource Management Methods in Telecommunications
   Haitao Tang, Sampsa Laine, Kimmo Raivio, and Olli Simula

29 PicSOM: Self-Organizing Maps for Content-Based Image Retrieval
   Erkki Oja, Jorma Laaksonen, Markus Koskela, Sami Brandt, Sami Laakso, and Ville Viitaniemi

30 Adaptive On-line Recognition of Handwritten Characters
   Erkki Oja, Jorma Laaksonen, Vuokko Vuori, Matti Aksela, and Jarmo Hurri

31 Texture Classification with Reduced Multidimensional Histograms
   Erkki Oja and Kimmo Valkealahti

32 Fault Analysis of Running Paper Web
   Jukka Iivarinen and Ari Visa

33 Attribute Trees in Image Analysis
   Markus Peura

34 Neural Methods for Analyzing Financial Information
   Kimmo Kiviluoto, Erkki Oja, Jyrki Maaranen, and Simona Mâlâroiu

35 Metrics that learn relevance
   Janne Sinkkonen and Samuel Kaski

36 Co-operation with Industry: the LIISA and IMPRESS Projects
   Erkki Oja

37 Self-Organizing Map in Matlab: the SOM Toolbox
   Juha Vesanto, Johan Himberg, Esa Alhoniemi, Kimmo Kiviluoto, Juha Parhankangas, and Jukka Parviainen

38 Workshops on Self-Organizing Maps
   Erkki Oja, Olli Simula, and Samuel Kaski

Theses 1997 - 1999

Publications 1997 - 1999