一种基于SFSVC算法的低复杂度分类器解决方案

2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE) Pub Date : 2017-10-01 DOI:10.1109/ISEEE.2017.8170696

Alin-Gabriel Cococi, Daniel Armanda, R. Dogaru, I. Dogaru

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引用次数: 0

摘要

将SFSVC (Super Fast Support Vector Classifier，超快速支持向量分类器)体系结构实现在计算移动平台上，并与其在经典机器(个人计算机)上的实现进行了性能评估。本文的目的是为了证明SFSVC架构可以利用其紧凑的结构和快速的算法在资源非常有限的环境下具有良好的性能。SFSVC不需要突触权重优化，其唯一可调的参数是基函数的半径和重叠参数。

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A low complexity classifier solution for mobile applications using SFSVC algorithm

The SFSVC (Super Fast Support Vector Classifier) architecture is implemented to a computational mobile platform and its performances are evaluated against its implementation on a classic machine (personal computer). The aim of this article is to prove that the SFSVC architecture can have good performances on an environment with very limited resources by taking advantages of its compact structure and fast algorithm. SFSVC does not need synaptic weights optimization, its only tunable parameters for a better generalization are the radius of the basis function and an overlapping parameter.

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2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE)

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