Functional Discrimination by Wavelets

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Functional Learning with Wavelets

Let X be a random variable taking values in L2 `

متن کامل

Brain Functional Connectivity Changes During Learning of Time Discrimination

The human brain is a complex system consist of connected nerve cells that adapts with and learn from the environment by changing its regional activities. Synchrony between these regional activities called functional network changes during the life, and with learning of new skills. Time perception and interval discrimination are among the most necessary skills for the human being to perceive mot...

متن کامل

Functional Supervised Classification with Wavelets

Let X be a random variable taking values in a Hilbert space and let Y be a random label with values in {0, 1}. Given a collection of classification rules and a learning sample of independent copies of the pair (X, Y ), it is shown how to select optimally and consistently a classifier. As a general strategy, the learning sample observations are first expanded on a wavelet basis and the overall i...

متن کامل

Clustering Functional Data Using Wavelets

We present two strategies for detecting patterns and clusters in high-dimensional timedependent functional data. The use on wavelet-based similarity measures, since wavelets are well suited for identifying highly discriminant local time and scale features. The multiresolution aspect of the wavelet transform provides a time-scale decomposition of the signals allowing to visualize and to cluster ...

متن کامل

Clustering Functional Data using Wavelets

This paper presents a method for effectively detecting patterns and clusters in high dimensional time-dependent functional data. It is based on waveletbased similarity measures since wavelets are ideal for identifying highly discriminant local time and scale features. We consider the contribution of each scale to the global energy, in the orthogonal wavelet transform of each input function to g...

متن کامل

ذخیره 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: Japanese journal of applied statistics

سال: 2005

ISSN: 0285-0370,1883-8081

DOI: 10.5023/jappstat.34.151