Unlock instant, AI-driven research and patent intelligence for your innovation.

Spiking neural network

A spiking neural network and spiking technology, applied in biological neural network models, neural architectures, neural learning methods, etc., can solve problems such as expensive computing, and achieve the effects of simplifying training and deployment time, low latency, and overcoming instability problems.

Pending Publication Date: 2021-08-20
INNATERA NANOSYSTEMS BV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, these techniques are computationally expensive when applied to deep, multilayer networks due to the complex causal relationships between neurons across different layers of the network.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Spiking neural network
  • Spiking neural network
  • Spiking neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0043] Certain embodiments are described in further detail below. However, it should be understood that these examples are not to be construed as limiting the scope of the present disclosure.

[0044] figure 1 is a simplified diagram of neural network 100 . Neurons 1 are connected to each other via synaptic elements 2 . In order not to clutter the image, only a small number of neurons and synaptic elements are shown (and only some have reference numbers attached to them). figure 1 The connection topology shown in , ie the way in which synaptic elements 2 connect neurons to each other 1 , is only an example and many other topologies can be employed. Each synaptic element 2 can transmit a signal to the input of a neuron 1 and each neuron 1 receiving the signal can process the signal and can subsequently generate an output which is transmitted via further synaptic elements 2 to other neurons 1 . Each synaptic element 2 has assigned to it a certain weight which is applied to ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

A spiking neural network for classifying input pattern signals, comprising a plurality of spiking neurons implemented in hardware or a combination of hardware and software, and a plurality of synaptic elements interconnecting the spiking neurons to form the network. Each synaptic element is adapted to receive a synaptic input signal and apply a weight to the synaptic input signal to generate a synaptic output signal, the synaptic elements being configurable to adjust the weight applied by each synaptic element, and each of the spiking neurons is adapted to receive one or more of the synaptic output signals from one or more of the synaptic elements, and generate a spatio-temporal spike train output signal in response to the received one or more synaptic output signals.

Description

technical field [0001] The present disclosure generally relates to composing spiking neural networks. The present disclosure relates more particularly, but not exclusively, to compositional pattern recognizers built from spiking neurons, and a system and method for compositionally building spiking neural networks using unique response methods. Background technique [0002] Automatic signal recognition (ASR) refers to the identification of signals by identifying their constituent features. ASR is used in a range of applications, such as recognizing speaker speech and spoken language in speech / voice recognition systems, identifying cardiac arrhythmias in electrocardiograms (ECG), determining the shape of gestures in motion control systems, and more. ASR is typically performed by characterizing the patterns present in short samples of the input signal, and thus accurate pattern recognition capabilities are fundamental to an effective ASR system. [0003] Measuring some physic...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06N3/063
CPCG06N3/049G06N3/088G06N3/063G06N3/045G06N3/08
Inventor S·S·库马尔A·齐亚约
Owner INNATERA NANOSYSTEMS BV