Physical neural network
Encyclopedia
A physical neural network is a type of artificial neural network
in which an electrically adjustable resistance material is used to emulate the function of a neural synapse
. "Physical" neural network is used to emphasize the reliance on physical hardware used to emulate neurons as opposed to software-based approaches which simulate neural networks. This terminology has been used to describe a type of artificial neural network patented by inventor Alex Nugent of KnowmTech in which neural synapses are based on variable resistance nanoconnections . More generally the term is applicable to other artificial neural networks in which a memristor
or other electrically adjustable resistance material is used to emulate a neural synapse.
and Ted Hoff developed ADALINE
(Adaptive Linear Neuron) which used electrochemical cells called memistors (memory transistors) to emulate synapses of an artificial neuron. The memistors were implemented as 3-terminal devices operating based on the reversible electroplating of copper such that the resistance between two of the terminals is controlled by the integral of the current applied via the third terminal. The ADALINE circuitry was briefly commercialized by the Memistor Corporation in the 1960’s enabling some applications in pattern recognition. However, since the memistors were not fabricated using integrated circuit fabrication techniques the technology was not scalable and was eventually abandoned as solid state electronics became mature.
describes a system of cortical computing with memristive nanodevices. The memristors (memory resistors) are implemented by thin film materials in which the resistance is electrically tuned via the transport of ions or oxygen vacancies within the film. DARPA’s SyNAPSE project
has funded IBM Research and HP Labs, in collaboration with the Boston University Department of Cognitive and Neural Systems (CNS), to develop neuromorphic architectures which may be based on memristive systems.
Artificial neural network
An artificial neural network , usually called neural network , is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an interconnected group of artificial neurons, and it processes...
in which an electrically adjustable resistance material is used to emulate the function of a neural synapse
Chemical synapse
Chemical synapses are specialized junctions through which neurons signal to each other and to non-neuronal cells such as those in muscles or glands. Chemical synapses allow neurons to form circuits within the central nervous system. They are crucial to the biological computations that underlie...
. "Physical" neural network is used to emphasize the reliance on physical hardware used to emulate neurons as opposed to software-based approaches which simulate neural networks. This terminology has been used to describe a type of artificial neural network patented by inventor Alex Nugent of KnowmTech in which neural synapses are based on variable resistance nanoconnections . More generally the term is applicable to other artificial neural networks in which a memristor
Memristor
Memristor is a passive two-terminal electrical component envisioned by Leon Chua as a fundamental non-linear circuit element relating charge and magnetic flux linkage...
or other electrically adjustable resistance material is used to emulate a neural synapse.
ADALINE
In the 1960's Bernard WidrowBernard Widrow
Bernard Widrow is a U.S. professor of electrical engineering at Stanford University. He is the co-inventor of the Widrow–Hoff least mean squares filter adaptive algorithm with his then doctoral student Ted Hoff...
and Ted Hoff developed ADALINE
ADALINE
ADALINE is a single layer neural network. It was developed by Professor Bernard Widrow and his graduate student Ted Hoff at Stanford University in 1960. It is based on the McCulloch–Pitts neuron...
(Adaptive Linear Neuron) which used electrochemical cells called memistors (memory transistors) to emulate synapses of an artificial neuron. The memistors were implemented as 3-terminal devices operating based on the reversible electroplating of copper such that the resistance between two of the terminals is controlled by the integral of the current applied via the third terminal. The ADALINE circuitry was briefly commercialized by the Memistor Corporation in the 1960’s enabling some applications in pattern recognition. However, since the memistors were not fabricated using integrated circuit fabrication techniques the technology was not scalable and was eventually abandoned as solid state electronics became mature.
Knowm
Alex Nugent describes a "Knowm" as a physical neural network including one or more nonlinear neuron-like nodes used to sum signals and nanoconnections formed from nanoparticles, nanowires, or nanotubes which determine the signal strength input to the nodes . Alignment or self-assembly of the nanoconnections is determined by the history of the applied electric field performing a function analogous to neural synapses.Phase change neural network
Stanford Ovshinsky describes an analog neural computing medium in which phase change material has the ability to cumulatively respond to multiple input signals . An electrical alteration of the resistance of the phase change material is used to control the weighting of the input signals.Memristive neural network
Greg Snider of HP LabsHP Labs
HP Labs is the exploratory and advanced research group for Hewlett-Packard. The lab has some 600 researchersin seven locations throughout the world....
describes a system of cortical computing with memristive nanodevices. The memristors (memory resistors) are implemented by thin film materials in which the resistance is electrically tuned via the transport of ions or oxygen vacancies within the film. DARPA’s SyNAPSE project
SyNAPSE
SyNAPSE is a DARPA program that aims to develop electronic neuromorphic machine technology that scales to biological levels. More simply stated, it is an attempt to build a new kind of computer with similar form, function, and architecture to the mammalian brain...
has funded IBM Research and HP Labs, in collaboration with the Boston University Department of Cognitive and Neural Systems (CNS), to develop neuromorphic architectures which may be based on memristive systems.
External links
- Interview with Alex Nugent on Knowm Neural Network October 26, 2002
- Information on DARPA's SyNAPSE project 2009