A stochastic resonator to detect BPAM signals ; analysis, PSR designs, and sine-induced SR

A Stochastic Resonator has been considered as an alternative signal processing tool because of its noise-induced performance enhancement ability. Here, the resonator parameters, steady states and transition time of the system are redefined for BPAM signals such that the region in which the resonator benefits from noise can be identified. Simple parameter-induced stochastic resonance (PSR) designs are then built, based on this analysis in order to configure the resonator in the optimum region. Furthermore, Sine-induced SR based on using a periodic signal instead of noise is introduced to enhance the system performance and compared with noise-enhanced SR (NSR). It is shown that Sine-induced SR provides a performance enhancement as it needs less power and does not require an adjustment relevant to the background noise. The results indicate that a resonator improves the receiver performance by eliminating noise if its parameters and BPAM characteristics are set accurately as given in the PSR designs, otherwise the resonator can benefit from either a noise as in NSR, or a sine wave as proposed

The design and analysis of quartic double well potential with stochastic resonance for communication systems

Non-linearity and noise are two phenomena that are expected to be essential to future advanced technologies. Although largely abstained, in general, from introduction into current communication systems, the counter-intuitive phenomenon called Stochastic Resonance (SR) can be introduced into communication systems in an innovative form. Therefore, in this thesis, the most prominent dynamical system in the SR field, the double well potential, namely the over-damped Duffing equation with symmetric bistable potential, has been studied in order to reveal its signal processing capabilities for communication systems. Within this thesis, the double well potential was designed in order to detect a binary pulse amplitude modulated (BPAM) signal subject to a background noise. The bit-error-rate (BER) performance was enhanced by adding various resonant signals to the input. In addition, the eye patterns of system output indicated that, while decreasing BER, a resonant causes a strong fluctuation. It was eliminated by a use of two systems coupled in parallel, which provided further performance improvement. The results inferred that the double well potential performs filtering and modulation. Following that, the double well potential was designed as a lowpass filter by determining the DC gain and cut-off frequency. Through simulations, as a filter, its noise suppression performance was shown to be better than that of various orders of Butterworth filters. The analog and digital modulation capabilities of the double well potential have also been investigated. In order to clarify the relation between input signal and modulation parameters, the differential equation driving the output was solved, and thus the output was expressed as a function of modulation parameters. It was shown that the output is a multivariate analog modulated signal. In terms of digital modulation, the output of system processing a PAM signal has been interpreted by means of a Markov chain. The results indicated that this process consists of a convolutional coding and multidimensional modulation. In addition, the presence of noise induced coding was found. Finally, the system was designed to obtain a pulse width position modulated (PWPM) output. Throughout the project, detection, filtering, modulation and coding capabilities have been demonstrated, it has been concluded that the double well potential is an sophisticated signal processing tool