From: marwan@ee.su.oz.au (Marwan A. Jabri, Sydney Univ. Elec. Eng., Tel: +61-2 692 2240)
Subject: MUME on DOS-5.0 is available for anonymous FTP
Reply-To: marwan@ee.su.oz.au (Marwan A. Jabri, Sydney Univ. Elec. Eng., Tel: +61-2 692 2240)
Organization: Electrical Engineering, The University of Sydney, Australia
Date: Sun, 10 Jan 1993 04:50:07 GMT

The Multi-Module Neural Computing Environment (MUME) version 0.5 for the
MSDOS platform is now available FREE of charge via anonymous ftp on
	brutus.ee.su.oz.au:/pub/MUME-0.5-DOS.zip

The full listing of the file is:
	-rw-r--r--  1 mume     mume      1391377 Jan  8 15:45 MUME-0.5-DOS.zip

Unzipping it should create a directory called MUME-DOS and it is about 4.6 MB.

Following is the README file.


Have fun.

MUME-Request@sedal.su.OZ.AU

-------------------------------------------------------------------------------

		Multi-Module Neural Computing Environment
				(MUME)
		    Version 0.5 (FREE) for MSDOS 5.0

MUME is a simulation environment for multi-modules neural computing. It
provides an object oriented facility for the simulation and training 
of multiple nets with various architectures and learning algorithms.

MUME includes a library of network architectures including feedforward,
simple recurrent, and continuously running recurrent neural networks.
Each architecture is supported by a variety of learning algorithms.

MUME can be used for large scale neural network simulations as it provides
support for learning in multi-net environments. It also provide pre and
post-processing facilities.

The object oriented structure makes simple the addition of new
network classes and new learning algorithms. New classes/algorithms can be
simply added to the library or compiled into a program at run-time. The
interface between classes is performed using Network Service Functions
which can be easily created for a new class/algorithm.

The architectures and learning algorithms currently available are:


	Class				Learning algorithms
	------------			-------------------

	MLP				backprop, weight perturbation,
					node perturbation, summed weight
					perturbation

	SRN				backprop through time, weight
					update driven node splitting,
					History bound nets 

	CRRN				Williams and Zipser

	Programmable
	Limited precision nets		Weight perturbation, Combined
					Search Algorithm, Simulated Annealing
		
	
Other general purpose classes include (viewed as nets):

	o	DC source
	o	Time delays
	o	Random source
	o	FIFOs and LIFOs
	o	Winner-take-all
	o	X out of Y classifiers

The modules are provided in a library. Several "front-ends" or clients are
also available.

MUME can be used to include non-neural computing modules (decision 
trees, ...) in applications.

The software is the product of a number of staff and postgraduate students
at the Machine Intelligence Group at Sydney University Electrical
Engineering. It is currently being used in research, research and
development and teaching, in ECG and ICEG classification, and speech and
image recognition. As such, we are interested in institutions that
can exploit the tool (especially in educational courses) and build up on it.

The software is written in 'C' and is aviable on the following platforms:
	- Sun (SunOS)
	- DEC (Ultrix)
	- Fujitsu VP2200 (UXP/M)
	- IBM RS6000 (AIX)
	- Hewlett Packard (HP-UX)
	- IBM PC compatibles (MSDOS 5.0) -- does not run under MS-Windows'
		DOS sessions

The MSDOS version of MUME is available as a public domain software. It can be
ftp-ed from brutus.ee.su.oz.au:/pub/MUME-0.5-DOS.zip.

MUME for the other platforms is available to research institutions on
media/doc/postage cost arrangements. Information on how to acquire it may be
obtained by writing (or email) to:

	Marwan Jabri
	SEDAL
	Sydney University Electrical Engineering
	NSW 2006 Australia
	Tel: (+61-2) 	692-2240
	Fax: 		660-1228
	Email:		marwan@sedal.su.oz.au


A MUME mailing list is currently available by sending an email to
	MUME-Requests@sedal.su.OZ.AU
Please put your subscription email address on the 'Subject:' line.

To send mail to everybody in the mailing list, send it to:
	 MUME@sedal.su.OZ.AU

All bugs reports should be sent to MUME-Bugs@sedal.su.OZ.AU and should include
the following details:
	1.  Date (eg. 12 Feb 1993).
	2.  Name (eg. John Citizen).
	3.  Company/Institution (eg. Sydney University Electrical Engineering).
	4.  Contact Address (eg. what-is-mume@sedal.su.OZ.AU).
	5.  Version of MUME (eg. MUME 0.5).
	6.  Machine Name/Type (eg. Sun Sparc 2).
	7.  Version of the Operating System (eg. SunOS 4.1.1).
	8.  Brief Description of the problem(s).
	9.  Error Messages (if any).
	10. Related Files (Filename, Version and Relationship to problems).

-------------------------------------------------------------------
Marwan Jabri				  Email: marwan@ee.su.oz.au
SEDAL, Electrical Engineering,		      Tel: (+61-2) 692-2240
Sydney University, NSW 2006, Australia 	      Fax: (+61-2) 692-3847
Newsgroups: comp.ai.neural-nets