(Digital Analog Neuro-fuzzy Implementation of Enhanced Learning Algorithms)

DANIELA is a Neuro-Fuzzy system for control applications. The system is based on a custom neural device that can implement either Multi-Layer Perceptrons, Radial Basis Functions or Fuzzy paradigms. The system implements intelligent control algorithms mixing neuro-fuzzy paradigms with finite state automatas and is used to control a walking hexapod.

DANIELA is the new version of the previous CINTIA board.


This section describes the architecture of AMINAH, the neuro-fuzzy processor used in DANIELA prototype board. AMINAH can operate with three different types of the WRBF algorithm; also it has an unlimited weight retention time (due to internal-refresh), a lower power consumption, and a high clock frequency.

Microphotograph of the AMINAH chip

AMINAH chip has two cascaded layers called hidden and output layer respectively. The architecture of one layer of AMINAH, is based on an NxM synaptic array and a vector of M neurons. Each neuron j is connected to a row of N synapses plus a threshold, while each column is connected to the same input Xi. The hidden layer has N=7 and M=16 while the output layer has N=15 and M=8.
Output signals are coded using Coherent Pulse Widht Modulation (CPWM), a particular Pulse Stream technique. Inputs signal Xi can either be analog or CPWM; in the former case, they are converted using internal Analog to CPWM converters.
The most important characteristics of AMINAH are:


A prototype board of the DANIELA system is currently under manifacturing. This board uses AMINAH as neuro-fuzzy processor and a commercial 68HC11 as general purpose processor. A 2Kbyte x 8 EEPROM is used as main memory and contains two memory blocks; each block consists in 512 bytes of synaptic weights (8 bit/weight) and other neural parameters (about 500 bytes), resulting in 1Kbyte per weight matrix.

Schematic diagram of DANIELA board

Most of the other logic circuits are implemented in an ALTERA EPM7128. A DAC800 D/A converter is used to write weights from the EEPROM to AMINAH. This prototype board includes also CPWM to Digital and Analog to Digital converters and power switching amplifiers for motor driving.
The host programming interface is realized under MATLAB where several custom C++ routines are used to download and receive data to/from DANIELA.

For more information look at the article presented at AT '96 - 1st International Symposium Workshop on Neuro-Fuzzy Systems, held in Lausanne (Switzerland) at the end of August 1996.

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Marcello Chiaberge
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