We propose two nonlinear Kalman smoothers that rely on Student’s t distributions. The T-Robust smoother finds the maximum a posteriori likelihood (MAP) solution for Gaussian process noise and Student’s t observation noise, and is extremely robust against outliers, outperforming the recently proposed `1-Laplace smoother in extreme situations (e.g. 50% or more outliers). The second estimator, whi...

In our previous research, we confirmed that the chaotic switching noise generated by the cubic map gained a good performance for solving combinatorial optimization problems when the noise was injected to the Hopfield neural network. However, the reason of the good effect of chaotic switching noise has not been clarified completely. In this study, we investigate the solving ability of Hopfield n...

We study the spatial distributions of two randomly interacting species, in the presence of an external multiplicative colored noise. The dynamics of the ecosystem is described by a coupled map lattice model. We find a nonmonotonic behavior in the formation of large scale spatial correlations as a function of the multiplicative colored noise intensity. This behavior is shifted towards higher val...

The noise-induced pattern formation in a population dynamical model of three interacting species in the coexistence regime is investigated. A coupled map lattice of Lotka-Volterra equations in the presence of multi-plicative noise is used to analyze the spatiotemporal evolution. The spatial correlation of the species concentration as a function of time and of the noise intensity is investigated...

A known jamming state information (JSI) scheme for a coded frequency-hopped M-ary frequency-shift-keying (FH/MFSK) system under partial-band noise jamming, plus additive white Gaussian noise, utilizes the maximum a posteriori (MAP) rule based on the total energy received in the M-tone signaling bands. It is assumed that the knowledge of partial-band noise jamming fraction is available to the JS...

This research uses a modified self-organized map to look for similarities and differences between noise signals and provides a context for unknown ones. The program first divides preprocessed data into quadrants in joint time-frequency domain and obtains the features. Features are also extracted in time domain, frequency domain, and joint time-frequency domain from noise files representing diff...

A coupled map lattice of generalized Lotka-Volterra equations in the presence of colored multiplicative noise is used to analyze the spatiotemporal evolution of three interacting species: one predator and two preys symmetrically competing each other. The correlation of the species concentration over the grid as a function of time and of the noise intensity is investigated. The presence of noise...

The ability to theoretically model the propagation of photon noise through PET and SPECT tomographic reconstruction algorithms is crucial in evaluating the reconstructed image quality as a function of parameters of the algorithm. In a previous approach for the important case of the iterative ML-EM (maximum-likelihood-expectation-maximization) algorithm, judicious linearizations were used to mod...

In the paper, a noise map service designated for the user interested in environmental noise is presented. Noise prediction algorithm and source model, developed for creating acoustic maps, are working in the cloud computing environment. In the study, issues related to the noise modelling of sound propagation in urban spaces are discussed with a particular focus on traffic noise. Examples of res...