Teaching wavelets with Java on the information superhighway

One of the most exciting new developments on the information superhighway is the Java language of the Sun Microsystem. Java is portable, powerful, and network-aware. This paper presents some ideas and experiments on teaching wavelets and signal processing using Java.

[1]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[2]  Amara Lynn Graps,et al.  An introduction to wavelets , 1995 .

[3]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  James H. McClellan,et al.  Multi-media and World Wide Web resources for teaching DSP , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[5]  R. Haddad,et al.  Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets , 1992 .

[6]  Don H. Johnson,et al.  The Signal Processing Information Base: a road to electronic information exchange , 1994, Proceedings of IEEE 6th Digital Signal Processing Workshop.

[7]  G. C. Orsak.  Teaching signal processing on the Information Superhighway , 1994, Proceedings of IEEE 6th Digital Signal Processing Workshop.

[8]  Jelena Kovacevic,et al.  Wavelets and Subband Coding , 2013, Prentice Hall Signal Processing Series.

[9]  David L. Donoho,et al.  De-noising by soft-thresholding , 1995, IEEE Trans. Inf. Theory.

[10]  Don H. Johnson,et al.  Distance teaming experiments in undergraduate DSP , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[11]  Y. Meyer,et al.  Wavelets and Filter Banks , 1991 .

[12]  Jerome M. Shapiro,et al.  Embedded image coding using zerotrees of wavelet coefficients , 1993, IEEE Trans. Signal Process..