• S+Wavelets is a commercial toolkit that allows users to apply wavelet analysis to an extremely broad range of problems involving signal, time series or image data.

Accomplishments

• The product is a module to the existing S-Plus software package that has been available commercially since 1995.
• As a module of S-Plus, S+Wavelets allows users to develop a thorough, penetrating analysis of signal, time series or image data. This tool kit offers more than 500 analysis functions within an object-oriented environment.
• S+Wavelets is available for both Unix and MS-Windows work stations.
• The book Applied Wavelet Analysis with S-Plus was written under the same SBIR Phase II.
• MathSoft is also leveraging the wavelets technology in a second commercial package—the Mathcad Wavelets Extension Pack, which provides engineers, scientists, statisticians and financial analysts with the mathematical and statistical routines they need to perform sophisticated analysis of signals and very large data sets. 

Commercialization

• S+Wavelets is being implemented as a module of the patented S-Plus software program, one of the most powerful data analysis software packages available today.
• The target audience is data analysts, scientists and engineers interested in the wavelet analysis of signals, time series, images and other technical and scientific data.
• S+Wavelets is sold separately or as an integrated portion of the S-Plus software package.
• From 1995 through January 1998, StatSci sold 526 units in the United States and approximately 155 units worldwide.
• Sales of Applied Wavelet Analysis with S-Plus has been more than 1,400 copies as of February 1998.

• The S+Wavelets module applications include signal processing, medical imaging, time series analysis, pattern recognition, non-linear signal estimation, data compression, and transformation of objects from one-dimensional to two-dimensional data.
• Other applications that it utilizes includes noise removal, time/frequency de-noising, fingerprint image compression and prototyping fast algorithms.
• Other features of the module that lead to other applications include: perfect reconstruction property; dual implementation in S-Plus and C languages; orthogonal and biorthogonal wavelets; the ability to create new wavelet filters; support for arbitrary signal/image sizes; range of boundary