survey performed by Juha Ikonen, May 21st 1999

Disclaimer: If any information on this page simply is not true, please tell us about it and we'll correct it ASAP.

Disclaimer: The opinions and observation herein should be considered personal of the person having performed by the survey, at the time of the survey. They do not reflect any official standing of his employer, of the Laboratory of Computer and Information Science or the Neural Networks Research Center.


Program name NeuroSolutions 3.020
Availability Commercial software, an evaluation version is available at

Prices vary from $195 to $1995 per seat.

Company information:
NeuroDimension, Inc.
1800 N. Main Street, Suite D4
Gainesville, FL 32609
Phone: 800-ND-IDEAS
Outside U.S.: 352-377-5144
Fax: 352-377-9009

Purpose Neural network simulation environment
Operating system Windows NT 3.51/4.0  or Windows 95/98
User interface Graphical user interface, macro language, OLE automation
Good in general
Good regarding the SOM
Documentation Extensive: an online help and a manual of over 700 pages.
  • The program uses an unique symbolism while presenting the structure of a neural network, which may seem cumbersome at first
  • User can add functionality to the program by creating custom DLL:s
  • The program can create ANSI-compatible C++ source code of a neural network which can be integrated into a C++ application.

SOM features

map parameters
Teaching algorithm [standard/batch/other] [is implementation correct?]
Map size 1- or 2-dimensional map grid

[biggest/smallest possible]

Map lattice and shape both rectangular
Neighborhood function Function type: line (two nearest nodes for 1D), diamond (four nearest nodes for 2D) or square (eight nearest nodes for 2D)
Neighborhood size (h): linear, exponential or logarithmic
Parameters: minimum and maximum values, update coefficient
Learning rate (alpha): linear, exponential or logarithmic
Parameters: minimum and maximum values, update coefficient
Initialization Uniformely distributed random values
Distance function Euclidian, dot product or box car (distance on a grid)
Unknown components [allowed or not]
Teaching length In epochs with stopping conditions
[Windows NT 4.0, 200 MHz Pentium MMX, 128 MB RAM]
[time for standard run]
Results [normal/strange] [quantization error, topographic error]
  • The SOM algorithm uses a conscience bias to determine the winning node, conscience parameters can be set by user
  • Synapse responses can be delayed

[Comments on SOM implementation]


Input formats [ascii/XLS/other]
Data handling and selection [scaling, histograms] [filters, conditions] [flexibility,usability]
Output formats [ascii/XLS/other]
Map measures [quantization error,topology error]
Labeling [no/simple/advanced]
Clustering [no/simple/advanced/by visualization]
Inspection of neurons [no/simple/advanced]
Clusters/map shape [u-matrix/clusters/projections (Sammon)/...]
Correlations [component planes/other]
Data projections [no/single/groups/advanced]
Markers [labels/...]
Monday, 09-Oct-2000 12:53:09 EEST