On the other hand, we will present other DIP tools, which are also derived from the Schrödinger equation. Such applications include signals intelligence and imagery intelligence. Thus a toolbox is completed, which it is essential for all applications of Digital Signal Processing (DSP) and Digital Image Processing (DIP) and, even, in the latter, BAT allows edge detection (which is called flank detection in case of signals), denoising, despeckling, compression, and superresolution of still images. In fact, BAT constitutes one side of a triangle (which from now on is closed) and it consists of the original signal in time, spectral analysis based on Fourier Theory and BAT. Even more, and unlike all derived tools from Fourier Theory (i.e., continuous, discrete, fast, short-time, fractional and quantum Fourier Transform, as well as, Gabor) BAT has the following advantages: a) compact support with excellent energy output treatment, b) low computational cost, O(N) for signals and O(N 2) for images, c) it doesn't have phase uncertainties (indeterminate phase for magnitude = 0) as Discrete and Fast Fourier Transform (DFT, FFT, respectively), d) among others. Besides, BAT is a metric, which assesses the impact of the flanks of a signal on its frequency spectrum, which is not taken into account by Fourier theory and even less in real time. In classic world is named bandwidth at time (BAT), which is presented here in opposition and as a complement of traditional spectral analysis frequency-dependent based on Fourier theory. A quantum time-dependent spectrum analysis, or simply, quantum spectral analysis (QuSA) is presented in this work, and it's based on Schrödinger equation, which is a partial differential equation that describes how the quantum state of a non-relativistic physical system changes with time.
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