The results of a series of theoretical studies are reported, examining the convergence rate for different approximate representations of α-stable distributions. Although they play a key role in modelling time-series with jumps and discontinuities, the use of α-stable distributions in inference often leads to analytically intractable problems. The infinite series representation employed in this ...

We consider Gaussian quantum circuits supplemented with non-Gaussian input states and derive sufficient conditions for efficient classical strong simulation of these circuits. In particular, we generalise the stellar representation continuous-variable to multimode setting relate rank states, a recently introduced measure non-Gaussianity, cost evaluating classically output probability densities ...

This paper presents a novel adaptive neuro-fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part. The capability of the proposed ANFIS2 for function approximation and dynamical system identification is remarkable. The structure of ANFIS2 is very sim...

An adaptive neuro fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part is presented in this paper. The capability of the proposed method (we named ANFIS2) for function approximation and dynamical system identification is remarkable. The structure o...