Detection of event-related potentials in individual subjects using support vector machines
نویسندگان
چکیده
منابع مشابه
Speech Event Detection Using Support Vector Machines
An effective speech event detector is presented in this work for improving the performance of speech processing systems working in noisy environment. The proposed method is based on a trained support vector machine (SVM) that defines an optimized non-linear decision rule involving the subband SNRs of the input speech. It is analyzed the classification rule in the input space and the ability of ...
متن کاملSTAGE-DISCHARGE MODELING USING SUPPORT VECTOR MACHINES
Establishment of rating curves are often required by the hydrologists for flow estimates in the streams, rivers etc. Measurement of discharge in a river is a time-consuming, expensive, and difficult process and the conventional approach of regression analysis of stage-discharge relation does not provide encouraging results especially during the floods. P
متن کاملDistinctive feature detection using support vector machines
An important aspect of distinctive feature based approaches to automatic speech recognition is the formulation of a framework for robust detection of these features. We discuss the application of the support vector machines (SVM) that arise when the structural risk minimization principle is applied to such feature detection problems. In particular, we describe the problem of detecting stop cons...
متن کاملRobust Anomaly Detection Using Support Vector Machines
Using the 1998 DARPA BSM data set collected at MIT’s Lincoln Labs to study intrusion detection systems, the performance of robust support vector machines (RSVMs) was compared with that of conventional support vector machines and nearest neighbor classifiers in separating normal usage profiles from intrusive profiles of computer programs. The results indicate the superiority of RSVMs not only in...
متن کاملMotion Detection Using Support Vector Machines
In this work we present an easy and efficient way to detect motion in an image sequence. This detection is useful to chose when is better to codify motion in order to reduce coding time and information to store. To decide whether there is motion or not, we must do a previous processing over each image to avoid confusion between illumination changes and motion. This processing tries to reduce th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Brain Informatics
سال: 2014
ISSN: 2198-4018,2198-4026
DOI: 10.1007/s40708-014-0006-7