Date: Tue, 19 Oct 1999 14:17:55 -0500 (CDT) X-Authentication-Warning: isip13.isip.msstate.edu: mantha set sender to mantha@isip.msstate.edu using -f From: Vishwanath Mantha To: picone@isip.msstate.edu In-reply-to: <199910191859.NAA01560@isip27.isip.msstate.edu> (message from Joe Picone - The Terminal Man on Tue, 19 Oct 1999 13:59:46 -0500 (CDT)) Subject: Re: abstract for ECE 8000 Reply-to: mantha@ISIP.MsState.EDU Content-Type: text Content-Length: 1441 > > Please resend me your abstract for your second talk for ECE 8000 > (involving factor analysis). Factor Analysis and MDS ------------------------- Factor Analysis(FA) is a technique that is often used to create new variables that summarize all of the information that might be available in the original variables. It is used to study relationships that might exist among the measured variables in a data set. Similar to PCA, it is a variable-directed technique. One basic objective of FA is to determine whether the response variables exhibit patterns or relationships with each other. While PCA produces an orthogonal transformation of the variables and does not depend on an underlying model, FA does depend on on a reasonable statistical model. Multidimensional scaling(MDS) is a mathematical technique that allows us to map the distances between points in a high dimensional space into a lower dimensional space. It is most useful when we can map into a two-dimensional space as this will help us visually confirm the different class groupings. The basic principle is to reduce distances between points in a two dimensional space. In this talk, we will cover the basic mathematical foundations of these two techniques and explore their applications in speech research. For eg., statistical pattern recognition techniques such as these are increasingly being used to differentiate between various phones. -Mantha