Sub-Optimum Signal Linear Detector Using Wavelets and Support Vector Machines

05/20/2005
by   Jaime Gomez, et al.
0

The problem of known signal detection in Additive White Gaussian Noise is considered. In previous work, a new detection scheme was introduced by the authors, and it was demonstrated that optimum performance cannot be reached in a real implementation. In this paper we analyse Support Vector Machines (SVM) as an alternative, evaluating the results in terms of Probability of detection curves for a fixed Probability of false alarm.

READ FULL TEXT
research
12/04/2009

Qualitative Robustness of Support Vector Machines

Support vector machines have attracted much attention in theoretical and...
research
05/20/2005

Upgrading Pulse Detection with Time Shift Properties Using Wavelets and Support Vector Machines

Current approaches in pulse detection use domain transformations so as t...
research
05/20/2005

Wavelet Time Shift Properties Integration with Support Vector Machines

This paper presents a short evaluation about the integration of informat...
research
02/22/2018

On detection of Gaussian stochastic sequences

The problem of minimax detection of Gaussian random signal vector in Whi...
research
04/08/2019

Early warning in egg production curves from commercial hens: A SVM approach

Artificial Intelligence allows the improvement of our daily life, for in...
research
05/12/2017

Iteratively-Reweighted Least-Squares Fitting of Support Vector Machines: A Majorization--Minimization Algorithm Approach

Support vector machines (SVMs) are an important tool in modern data anal...
research
03/29/2019

Neuromorphic In-Memory Computing Framework using Memtransistor Cross-bar based Support Vector Machines

This paper presents a novel framework for designing support vector machi...

Please sign up or login with your details

Forgot password? Click here to reset