Research before 1996

List of former publications

Former directions of research

Former activities include hardware accelerators, in particular the Mantra machine. The projects which have been finished by 1996 are reviewed below.
  1. Hardware for Auditory System.. Can we model the first few processing from the cochlea to spiking neurons by simple hardware modules? What are the effects of non-linear and adaptive mechanisms on the performance of the cochlear preprocessing? What is the relevance of phase locking with spiking neurons for pitch detection? The project is supervised by Prof. E. Vittoz, from the Electronics Laboratory (EPFL-DE) and Swiss Centre for Electronics and Micromechanics (CSEM). Potential Applications of auditory preprocessing to speech recognition are studied in a joint project with Prof. M. Hasler from the Circuit and Systems Laboratory. The project ended in 1998.
  2. Neural Network Algorithms Two directions of research have been selected: self-organizing feature maps and multilayer perceptrons. For the Kohonen model many interesting theoretical questions are still open, e.g., convergence criteria and best distance measure. Multilayer networks with discrete outputs and/or weights are investigated using tools from discrete mathematics. In particular, the computational power of such models has been analyzed and new combinational optimization algorithms have been proposed. New methods for constructing and training multilayer networks with continuous and discrete weights have also been developed. They are better suited for large size problems because they involve local computations; in addition, convergence is faster than standard techniques such as back-propagation.
  3. Neural Network Accelerators Digital neural network systems - also named neuro-accelerators - are usually linked to a workstation, or used as a computation server on a local network. Neuro-accelerators are absolutely necessary to progress in neural network research, especially if real time performance is important.

    A systolic architecture has been selected for building an accelerator based on VLSI dedicated chips. Three generations of VLSI circuits, adequate for Hopfield, Kohonen and back-propagation have been designed. The MANTRA I machine constructed at the Centre Mantra features a peak performance of 400 MCPS. The project ended in 1996

  4. Applications of Neural Networks Several applications are under way and are listed below. Due to hardware and software evolution, and to new neural network algorithms, it is considered important that the implementation of an application does not take more than two years.
    1. Security of electric power systems The application of a Kohonen network for the security of electric power systems is one possible approach for defining limits of safe operations.
    2. Meteorological observation The Swiss Institute of Meteorology is concerned by recognizing meteorological situations next to airports. The AMETIS I system is partly manual; a neural network updated with 30 values every 30 seconds is planned to help the expert system to take the best decisions.

The MANTRA I Machine

Features

Description

Based on a 2D systolic array of processing elements, the MANTRA I machine is a high-performance low-cost neurocomputer capable of working on any size neural network. Hooked to a SUN SPARCstation via the SBus interface, it can directly access the computer central memory and accelerate the neural computation by a factor of 100.

Software

The MANTRA I machine will be programmed through a library of C routines dedicated to the selected models. Graphic interaction will be provided for experimental purposes.

Applications

Designed to be applied to on-line control systems, it is particularily suited for applications requiring fast learning of large artificial neural networks. This is important for robotic applications, artificial vision, etc.

Get some images of the machine