Machine learning for audio, image and video analysis by Camastra F., Vinciarelli A.

By Camastra F., Vinciarelli A.

Concentrating on complicated media and the way to transform uncooked facts into worthwhile info, this ebook bargains either introductory and complicated fabric within the mixed fields of desktop studying and image/video processing. it's prepared into 3 elements. the 1st makes a speciality of technical features, easy mathematical notions and ordinary computer studying suggestions. the second one presents an intensive survey of so much suitable laptop studying innovations for media processing. The 3rd specializes in purposes and indicates how suggestions are utilized in real difficulties. Examples and difficulties are in response to info and software program applications publicly on hand on the internet.

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6 times. Incoming sounds penetrate into the cochlea through the oval window and propagate along the basilar membrane (BM), an elastic membrane that follows the spiral tube from the base (in correspondence of the oval window) to the apex (at the opposite extreme of the tube). In the presence of incoming sounds, the BM vibrates with an amplitude that changes along the tube. At the base the amplitude is at its minimum and it increases constantly until a maximum is reached, after which point the amplitude decreases quickly so that no more vibrations are observed in the rest of the BM length.

When air arrives at the glottis, the pressure difference with respect to the vocal tract increases until the vocal folds are forced to open to reestablish the equilibrium. When this is reached, the vocal folds close again and the cycle is repeated as long as voiced phonemes are produced. The vibration frequency of the vocal folds is a characteristic specific of each individual and it is called fundamental frequency F 0, the single factor that contributes more than anything else to the voice pitch.

1. e. one with a zero power spectrum for frequencies f > fmax ) baseband (f > 0) signal to be reconstructed fully, it must be sampled at a rate F ≥ 2fmax . 6 shows what happens when the above condition is met (first and second plot from above) and when is not (third and fourth plot from above). 26) is important because the overlapping between Sp (Ω) replications is the frequency domain effect of the aliasing. In other words, the aliasing can be avoided if signals are sampled at a rate F higher or equal than the double of the highest frequency fmax .

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