2019
DOI: 10.1155/2019/8212867
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A Novel Hardware Systolic Architecture of a Self-Organizing Map Neural Network

Abstract: In this article, we propose to design a new modular architecture for a self-organizing map (SOM) neural network. The proposed approach, called systolic-SOM (SSOM), is based on the use of a generic model inspired by a systolic movement. This model is formed by two levels of nested parallelism of neurons and connections. Thus, this solution provides a distributed set of independent computations between the processing units called neuroprocessors (NPs) which define the SSOM architecture. The NP modules have an in… Show more

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Cited by 9 publications
(12 citation statements)
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“…SOM is made up of a single layer of neurons in one (1D) or two-dimensional (2D) grid (Ben et al ., 2019). Each neuron on the grid represents an n-dimensional weight vector where n is the dimension of the input data to the SOM network.…”
Section: Key Technologies and Architecturesmentioning
confidence: 99%
“…SOM is made up of a single layer of neurons in one (1D) or two-dimensional (2D) grid (Ben et al ., 2019). Each neuron on the grid represents an n-dimensional weight vector where n is the dimension of the input data to the SOM network.…”
Section: Key Technologies and Architecturesmentioning
confidence: 99%
“…In addition, hardware implemented ANNs allow for specific optimization of the structure of particular components. This leads to a significant reduction in energy consumption and the device miniaturization that translates into cost reduction [19,[21][22][23][24][25][26][27].…”
Section: Introductionmentioning
confidence: 99%
“…A new modular architecture for a SOM called systolic-SOM (SSOM) which is based on the use of a generic model inspired by a systolic movement was proposed by Khalifa et al [24]. The model was formed by two levels of nested parallelism of neurons and connections that provided a distributed set of independent computations between the processing units.…”
mentioning
confidence: 99%