• Design and Analysis of Binary Scalar Quantizer of Laplacian Source with Applications 

      Perić, Zoran; Denić, Bojan; Savić, Milan; Despotović, Vladimir (MDPI, 2020-10-27)
      A compression method based on non-uniform binary scalar quantization, designed for the memoryless Laplacian source with zero-mean and unit variance, is analyzed in this paper. Two quantizer design approaches are presented ...
    • Design of a 2-Bit Neural Network Quantizer for Laplacian Source 

      Perić, Zoran; Savić, Milan; Simić, Nikola; Denić, Bojan; Despotović, Vladimir (Molecular Diversity Preservation International, 2021-07-22)
      Achieving real-time inference is one of the major issues in contemporary neural network applications, as complex algorithms are frequently being deployed to mobile devices that have constrained storage and computing power. ...
    • Speaker Recognition Using Constrained Convolutional Neural Networks in Emotional Speech 

      Simić, Nikola; Suzić, Siniša; Nosek, Tijana; Vujović, Mia; Perić, Zoran; Savić, Milan; Delić, Vlado (Molecular Diversity Preservation International, 2022-03-16)
      Speaker recognition is an important classification task, which can be solved using several approaches. Although building a speaker recognition model on a closed set of speakers under neutral speaking conditions is a ...