Publication

Hardware spiking neural network with run-time reconfigurable connectivity in an autonomous robot

Dario Floreano, Yann Thoma, Daniel Roggen
2003
Conference Papers

Abstract

A cellular hardware implementation of a spiking neural network with run-time reconfigurable connectivity is presented. It is implemented on a compact custom FPGA board which provides a powerful reconfigurable hardware platform for hardware and software design. Complementing the system, a CPU synthesized on the FPGA takes care of interfacing the network with the external world. The FPGA board and the hardware network are demonstrated in the form of a controller embedded on the Khepera robot for a task of obstacle avoidance. Finally, future implementations on new multi-cellular hardware are discussed.

Official source

https://infoscience.epfl.ch/entities/publication/db6c991e-1895-4fd6-a92e-4e4c1665c7f9

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Dario Floreano, Yann Thoma, Daniel Roggen
2003
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/db6c991e-1895-4fd6-a92e-4e4c1665c7f9

About this result

Related concepts (32)

Computer hardware

Computer hardware includes the physical parts of a computer, such as the case, central processing unit (CPU), random access memory (RAM), monitor, mouse, keyboard, computer data storage, graphics card, sound card, speakers and motherboard. By contrast, software is the set of instructions that can be stored and run by hardware. Hardware is so-termed because it is "hard" or rigid with respect to changes, whereas software is "soft" because it is easy to change. Hardware is typically directed by the software to execute any command or instruction.

Field-programmable gate array

A field-programmable gate array (FPGA) is an integrated circuit designed to be configured after manufacturing. The FPGA configuration is generally specified using a hardware description language (HDL), similar to that used for an application-specific integrated circuit (ASIC). Circuit diagrams were previously used to specify the configuration, but this is increasingly rare due to the advent of electronic design automation tools. FPGAs contain an array of programmable logic blocks, and a hierarchy of reconfigurable interconnects allowing blocks to be wired together.

Spiking neural network

Artificial neural network Spiking neural networks (SNNs) are artificial neural networks that more closely mimic natural neural networks. In addition to neuronal and synaptic state, SNNs incorporate the concept of time into their operating model. The idea is that neurons in the SNN do not transmit information at each propagation cycle (as it happens with typical multi-layer perceptron networks), but rather transmit information only when a membrane potential—an intrinsic quality of the neuron related to its membrane electrical charge—reaches a specific value, called the threshold.

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Hardware spiking neural network with run-time reconfigurable connectivity in an autonomous robot

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