The restart of the receiver will lead to change in non-overlapping frequency inter-system biases (ISB), which make it difficult apply tightly combined RTK method pre-calibrating ISB actual scene. Particle swarm optimization (PSO) algorithm can be used estimate fractional part phase bias (F-ISPB) real time, is not affected by restart. However, standard PSO easily fall into local optimum and cann...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...

In general, ray paths in anisotropic media can be found by solving the sixth-order kinematic ray equations. In this paper it is shown that in media where the density-normalized elastic parameters depend quadratically on one coordinate, i.e. the velocities vary linearly, the projection of the ray path on to the slowness vector plane, which is fixed, is the same shape as the cross-section of the ...

In contrast to the equivalence of linear blind source separation and linear independent component analysis it is not possible to recover the original source signal from some unknown nonlinear transformations of the sources using only the independence assumption. Integrating the objectives of statistical independence and temporal slowness removes this indeterminacy leading to a new method for no...

Understanding the guiding principles of sensory coding strategies is a main goal in computational neuroscience. Among others, the principles of predictive coding and slowness appear to capture aspects of sensory processing. Predictive coding postulates that sensory systems are adapted to the structure of their input signals such that information about future inputs is encoded. Slow feature anal...

The problem of adaptive estimation of regression function from noisy observations is considered in the paper. We provide an adaptive confidence set B̂N of level 1− α, 0 < α < 1, for the unknown function f . Here B̂N is a L2-ball of (random) diameter τ̂N , centered at the wavelet adaptive estimate f̂N . We show that if it is known a priori that f belongs to a Besov functional class F∗, then the prop...

A new definition of Adaptive Neuro Fuzzy Systems is presented in this paper for the identification of unknown nonlinear dynamical systems. The proposed scheme uses the concept of Adaptive Fuzzy Systems (AFS) operating in conjunction with High Order Neural Network Functions (F-HONNFs). Since the plant is considered unknown, we first propose its approximation by a special form of an adaptive fuzz...