๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Data over voice using time-warping technique

โœ Scribed by Dov Wulich; Moshe Bukris


Publisher
Elsevier Science
Year
1993
Tongue
English
Weight
586 KB
Volume
34
Category
Article
ISSN
0165-1684

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Embedding of time series data by using d
โœ Yuko Mizuhara; Akira Hayashi; Nobuo Suematsu ๐Ÿ“‚ Article ๐Ÿ“… 2006 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 807 KB

## Abstract We propose an approach to embedding time series data in a vector space based on the distances obtained from Dynamic Time Warping (DTW), and classifying them in the embedded space. Under the problem formulation in which both labeled data and unlabeled data are given beforehand, we consid

Time and Space Optimal Data Parallel Vol
โœ Craig M. Wittenbrink; Arun K. Somani ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 708 KB

In this paper we present a data parallel volume rendering algorithm that possesses numerous advantages over prior published solutions. Volume rendering is a three-dimensional graphics rendering algorithm that computes views of sampled medical and simulation data, but has been much slower than other

Integration of voice/data services over
โœ Jyh-Horng Wen; Jee-Wey Wang; Jyh-Yeuan Chang ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 188 KB

The integration of voice and data services over PACS systems using a movable boundary scheme is studied. First, we use the theory of discrete-time Markov chain to analyse the system; then, an approximate analysis using the continuous-time Markov chain model is conducted. For the initial access of vo

Reduced-Order Estimation Technique Using
โœ Seiichi Nakamori ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 182 KB

This paper proposes reduced-order estimation technique by the recursive least-squares filter and fixed-point smoother in linear discrete-time systems, given output measurement data. The estimators require the information of the system matrix, the observation vector of the signal generating model and