Now showing items 1-4 of 4

  • Thumbnail

    Adaptive Two-stage Spectrum Sensing under Noise Uncertainty in Cognitive Radio Networks 

    Kornkamol Thakulsukannant; Wilaiporn Lee; Akara Prayote; Kanabadee Srisomboon (2016)

    To utilize licensed spectrum bands efficiently, spectrum sensing needs to be accurate and fast. The occurrence of noise uncertainty and the lower in received PU signal power due to the distance between the transmitter and the receiver, path loss, are the main challenges that has a great impact on the accuracy of spectrum sensing. In this paper, we propose a new scheme of two-stage spectrum sensing, “Adaptive Two-stage Spectrum Sensing (ATSS)”, under noise uncertainty environment. ATSS is a modified of a conventional two-stage spectrum sensing ...
  • Thumbnail

    An Alternative Single-Image Super Resolution Framework Employing High Frequency Prediction Using A Robust Huber Rational Function 

    Kornkamol Thakulsukannant; Vorapoj Patanavijit (2015-11)

    In general prospective, SI-SR or Single-Image Super-Resolution, which is one of the most useful algorithms of Super Resolution-Reconstruction (SRR) algorithms, is a mathematical procedure for acquiring a high-resolution image from only one coarse-resolution image, which is usually computed by Digital Image Processing (DIP). Even thought there have been substantially researched during the last decade, Single - Image Super-Resolution for applying on real implementations still keeps throw down the gauntlet. One of the practical Single- Image ...
  • Thumbnail

    Practical Programming Tutorial of Two Dimensional Discrete Fourier Transform (DFT) Based on MATLAB® for Both 2D Signals and Images 

    Kornkamol Thakulsukannant; Vorapoj Patanavijit (2016)

    The two-dimensional (2-D) Discrete Fourier Transform (DFT) and Inverse Discrete Fourier Transform (IDFT) represent mathematical models for 2-D signals (such as digital images and digital videos) in the frequency and spatial domains, respectively. Digital Image Processing (DIP) has been implemented globally over the past two decades. Thus, 2-D Discrete Fourier Transform (2-D DFT) is essential in terms of representing mathematical models and analyzing 2-D signals and systems. In light of its importance, this article presents a tutorial for ...
  • Thumbnail

    Tutorial of One Dimensional Discrete Fourier Transform (DFT): Theory, Implementation and MATLAB® programming 

    Kornkamol Thakulsukannant; Vorapoj Patanavijit (2015)

    The Discrete Fourier Transform (DFT) and Inverse Discrete Fourier Transform (IDFT) are classical approaches to mathematically model signals and systems in the frequency and spatial (or temporal) domains, respectively. Due to worldwide implementation of Digital Signal Processing (DSP) during the last two decades, Discrete Fourier analysis has become one of the most useful mathematical techniques for analyzing digital signals and systems. Consequently, this article provides a tutorial for the Discrete Fourier Transform (DFT) on 1- dimensional (1-D) ...