MOOC
Information, Calcul, Communication: Introduction à la pensée informatique
Lectures in this MOOC (38)
Signals, Frequencies and BandwidthMOOC: Information, Calcul, Communication: Introduction à la pensée informatique
Introduces signals, frequencies, and bandwidth, including pure sinusoids, Fourier theory, and spectral representation.
Signal FilteringMOOC: Information, Calcul, Communication: Introduction à la pensée informatique
Explores signal filtering using low-pass filters to reduce noise and distortions in signals, showcasing frequency suppression and smoothing effects.
Signal SamplingMOOC: Information, Calcul, Communication: Introduction à la pensée informatique
Explores representing analog signals digitally through sampling and quantization, discussing sampling frequency, undersampling consequences, and the stroboscopic effect.
Signal Reconstruction: BasicsMOOC: Information, Calcul, Communication: Introduction à la pensée informatique
Explores signal reconstruction basics, including interpolation techniques and formulas using triangular and sinc functions.
Sampling TheoremMOOC: Information, Calcul, Communication: Introduction à la pensée informatique
Explores the sampling theorem, illustrating signal reconstruction and the importance of meeting the Nyquist criterion.
Filtering before SamplingMOOC: Information, Calcul, Communication: Introduction à la pensée informatique
Emphasizes the necessity of filtering signals before sampling to prevent undersampling effects.
Compression: introductionMOOC: Information, Calcul, Communication: Introduction à la pensée informatique
Introduces data compression, exploring how redundancy in data can be reduced to achieve smaller file sizes without losing information.
Entropy: Examples and PropertiesMOOC: Information, Calcul, Communication: Introduction à la pensée informatique
Explores examples of guessing letters, origins of entropy, and properties in information theory.
Lossless Compression: Shannon-Fano and HuffmanMOOC: Information, Calcul, Communication: Introduction à la pensée informatique
Explores lossless compression using Shannon-Fano and Huffman algorithms, showcasing Huffman's superior efficiency and speed over Shannon-Fano.
Shannon's TheoremMOOC: Information, Calcul, Communication: Introduction à la pensée informatique
Introduces Shannon's Theorem on binary codes, entropy, and data compression limits.