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Neuromorphic processing apparatus

A neuron, preprocessor technology, applied in the field of devices such as spiking neural networks, which can solve problems such as increasing complexity

Pending Publication Date: 2020-04-10
SAMSUNG ELECTRONICS CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Multi-unit approach adds complexity
In these approaches, asymmetric conductance response may remain a problem, and differential configuration requires cyclic rebalancing of synapses to prevent cell saturation

Method used

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  • Neuromorphic processing apparatus
  • Neuromorphic processing apparatus
  • Neuromorphic processing apparatus

Examples

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Embodiment Construction

[0025] Detailed examples of claimed structures and devices are disclosed herein; however, it is to be understood that the disclosed embodiments are merely illustrations of the claimed structures and methods that can be embodied in various forms. This invention may, however, be embodied in many different forms and should not be construed as limited to the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. In the description, details of well-known features and techniques may be omitted to avoid unnecessarily obscuring the presented embodiments.

[0026] figure 1 is a schematic block diagram showing the basic structure of the neuromorphic processing device 1 embodying the present invention. In this example, the device 1 is used for an image classification application. The device 1 comprises a pre-processor un...

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Abstract

Neuromorphic processing apparatus is provided. The present invention may include a spiking neural network comprising a set of input spiking neurons each connected to each of a set of output spiking neurons via a respective synapse for storing a synaptic weight which is adjusted for that synapse in dependence on network operation in a learning mode of the apparatus, and each synapse is operable toprovide a post-synaptic signal, dependent on its synaptic weight, to its respective output neuron. The present invention may further include a pre-processor unit adapted to process input data, defining a pattern of data points, to produce a first set of input spike signals which encode values representing respective data points, and a second set of input spike signals which encode values complementary to respective said values representing data points, and to supply the input spike signals to respective predetermined input neurons of the network.

Description

Background technique [0001] The present invention relates generally to neuromorphic processing devices, and more particularly to such devices employing spiking neural networks. [0002] Neuromorphic technologies involve computing systems inspired by the biological architecture of the nervous system. Traditional computing architectures are becoming increasingly inadequate to meet the ever-expanding processing demands placed on modern computer systems. For example, the growth of Big Data (BigData) requires high-speed processing of ever-increasing amounts of diverse information. Compared to the human brain, traditional von Neumann computer architectures are very inefficient in terms of power consumption and space requirements. The human brain occupies less than 2 liters and consumes about 20W of power. Using a state-of-the-art supercomputer to simulate 5 seconds of brain activity takes about 500 seconds and requires 1.4MW of power. These problems have prompted significant res...

Claims

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Application Information

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IPC IPC(8): G06N3/063
CPCG06N3/049G06N3/088G06N3/065G06N3/082
Inventor S·西德尔S·沃茨尼亚克A·潘塔兹
Owner SAMSUNG ELECTRONICS CO LTD
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