A new algorithm for learning invariance manifolds is introduced that allows a neuron to learn a non-linear transfer function to extract invariant or rather slowly varying features from a vectorial input sequence. This is generalized to a group of neurons, referred to as a Gibson-clique, to learn slowly varying features that are uncorrelated. Since the transfer functions are non-linear, this tec...

The non-linear effects operating at the recombination epoch generate a non-Gaussian signal in the CMB anisotropies. Such a contribution is relevant because it represents a major part of the secondorder radiation transfer function which must be determined in order to have a complete control of both the primordial and non-primordial part of non-Gaussianity in the CMB anisotropies. We provide an e...

The state feedback regulator problem for a network of countercurrent heat exchangers is considered in this article. The system is described by two sets of hyperbolic partial differential equations (PDEs) and the model is nonlinear with respect to the control input. To deal with the nonlinearity, the equilibrium temperature profile is calculated and utilized in the linearization of the original ...

When a signal goes through a system having a static, nonlinear transfer function, the output signal will be distorted. In addition to it, the detected output signal is usually contaminated by noise, due to the noisy environment. If we compensate the nonlinearity with its inverse, the expected value of the output signal will be different from it's original one, due to the nonlinearly distorted n...

A family of algorithms for the identification of continuous-time nonlinear plants operating in closed loop is presented. An adjustable closed-loop output error-type predictor parameterized in terms of the existing controller and the estimated plant model is used. The algorithms are derived from stability considerations in the absence of noise and assuming that the plant model is in the model se...

An attempt is made to unravel the dual influences of seawater temperature and isotopic composition upon the oxygen-isotope records of benthic foraminifers from the deep Pacific (dOb). Our approach is to estimate a non-linear transfer function between past sea level and dOb over the last two glacial cycles, with additional information from the mid-Pliocene. Combining this transfer function with ...

The problem of modelling and simulating pipelines that are used for transporting different fluids is addressed in the paper. The problem is solved by including fluid density in the model beside pressure and velocity of the medium. First, the system of nonlinear partial differential equations is derived. Then, the obtained model is linearised and transformed into the transfer function form with ...

In Nonlinear Dynamics synchronization of oscillators is examined. Alternatively for linear stochastic systems, coherence analysis is utilized to detect interdependencies in transfer function systems. In contrast to the latter, oscillators continue oscillating in the absence of interaction between the processes. For transfer function systems the output ceases to exist without an input. Analysis ...

Most existing cross-domain recommendation algorithms focus on modeling ratings, while ignoring review texts. The review text, however, contains rich information, which can be utilized to alleviate data sparsity limitations, and interpret transfer patterns. In this paper, we investigate how to utilize the review text to improve cross-domain collaborative filtering models. The challenge lies in t...

Several optimal three-dimensional orbital transfer problems are solved for thrust-limited spacecrafts using collocation and nonlinear programming techniques. The solutions for full nonlinear equations of motion are obtained where the integrals of the free Keplerian motion in three dimensions are utilized for coasting arcs. In order to limit the solution space, interior-point constraints are use...