Reproducible Research Section

Here are some Matlab and Python codes related to my research and publications. Codes written with my PhD students are also available on the ISPGroup Data/Software page.

• IPython notebooks for testing the results of "A Quantized Johnson Lindenstrauss Lemma: The Finding of Buffon's Needle". As explained on this related blog post, there are two such notebooks: "Testing a quasi-isometric quantized embedding" and "Testing a quasi-isometric quantized embedding with percentile analysis".
• "Quantized Iterative Hard Thresholding algorithm Demo" associated to the paper "Quantized Iterative Hard Thresholding: Bridging 1-bit and High-Resolution Quantized Compressed Sensing" by Laurent Jacques, Kévin Degraux, Christophe De Vleeschouwer, arXiv:1305.1786.
• "Robust 1-Bit Compressive Sensing Demo" associated to the paper "Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors" by L. Jacques, J. N. Laska, P. T. Boufounos, and R. G. Baraniuk (abstract and preprint, arXiv:1104.3160)
• Simple Matlab codes to test the Geometrically optimized Matching Pursuit introduced in "A Geometrical Study of Matching Pursuit Parametrization" (Zip archive, Updated: 4 Nov. 2008)
• A Fast (1-D and 2-D) Noiselet Transform (last version: April 21, 2008).
  Slight Variation of this Walsh-Hadamard Transform.
  The Noiselet Transform has been designed in :
  R. Coifman, F. Geshwind, and Y. Meyer. Noiselets. Appl. Comput. Harmon. Anal., 10(1):27--44, 2001.
• The YAWTb Toolbox (Yet Another Wavelet Toolbox, mainly for continuous transforms)
• The Basis Pursuit De Quantization (BPDQ) toolbox by D. Hammond, M.J. Fadili and I.