In this paper, the feasibility of replacing a chaos source by an equivalent digital pseudo-random Generator realized using Linear Feedback Shift Register (LFSR) is studied. Particular emphasis is given on the digital implementation Piece-Wise Linear A ffine Maps (PWAM). As an application, an FPGA implementation of four different maps has been experimentally verifi ed in a FM-DCSK test radio system.
Feeding antennas with proper signals can be difficult. The signal is often described as a voltage, and voltages are not well defined in electromagnetic wave formulations. There are several tricks to model voltage Generators in such situations, and one is the magnetic frill. This model shows the basic steps of defining a magnetic frill voltage Generator for a dipole antenna, and it also compares the resulting antenna impedance with known results.
Feeding antennas with proper signals can be difficult. The signal is often described as a voltage, and voltages are not well defined in electromagnetic wave formulations. There are several tricks to model voltage Generators in such situations, and one is the magnetic frill. This model shows the basic steps of defining a magnetic frill voltage Generator for a dipole antenna, and it also compares the resulting antenna impedance with known results.
Image enhancement in frequency domain using Fourier center frequency, Gaussian lowpass filter, Low pass filter, high pass filter. Image restoration using medean filter, weiner filter with noise Generator such as Gaussian noise, Salt and Pepper noise
Hardware random number Generators attempt to extract
randomness directly from complex physical systems. In this way they create random outputs without requiring any seed inputs. In this paper we describe how to use Physical Random Functions (or Physical Unclonable Functions, PUFs) to create a candidate hardware random number Generator.
