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    • Multimedia Signal Processing

      This module covers the fundamental tools for digital signal processing. In particular it addresses topics of signal analysis and filtering concerning audio and image data both from the deterministic and the statistical viewpoint.

       

      Participants will learn basic tools for digital signal filtering and analysis. In particular the program will be articulated in the following parts:

      Part I: Fundamentals of digital signal processing

      Introduction to the DFT:

      DFT, IDFT, derivation of the DFT, Fourier theorems for the DFT

       

      Introduction to digital filters:

      Time-domain representations, transfer function analysis, frequency response analysis

       

      Windowing and STFT:

      Overview of windows, overlap and add, STFT

       

      Digital filter design techniques:

      Filter specifications, IIR filter design, FIR filter design

       

      Introduction to multirate processing:

      Downsamplig, upsampling, decimation, interpolation, polyphase filters, perfect reconstruction filter banks. 

        

      Part II: Fundamentals of statistical signal processing

       

      Random sequences:

      Expectations, i.i.d. sequences, jointly distributed random sequences, correlation and covariance sequences, time averages and ergodicity.

       

      Spectral estimation:

      Introduction to estimation theory, estimate bias and variance, maximum likelihood estimation, Bayesian estimation, power spectral density, nonparametric spectral estimation, parametric spectral estimation.

       

      Linear prediction:

      Autocorrelation and autocovariance methods, frequency domain interpretation of linear prediction.

       

      Wiener filtering:

      Principle of orthogonality, Wiener-Hopf equations, non-causal and causal Wiener filtering, applications to denoising, echo cancellation and channel equalization.

       

      Laboratory activities

      Laboratory activities enable student to improve their understanding of the concepts learnt during the lectures. The proposed examples of applications and exercises, cover audio, image and video processing, and are based on Matlab®

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    • Fondamenti di Telecomunicazioni
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