Blind source separation problem has recently received a great deal of attention in signal processing and unsupervised neural learning. In the current approaches, the additive noise is negligible so that it can be omitted from the consideration. To be applicable in realistic scenarios, blind source separation approaches should deal evenly with the presence of noise. In this contribution, a novel...

In 1972, Forney proposed a maximum likelihood sequence estimator for digital PAM (pulse amplitude modulated) signals in the presence of nite intersymbol interference (ISI) and additive white Gaussian noise. This optimum scheme involves passing the received signal through a so-called whitened linear matched lter, sampling the lter output at the symbol rate, and processing the resulting sequence ...

the present study was carried out to compare different random regression models to estimate variance components of lamb's average birth weight per lambing (abwll) in mehraban sheep. the data were 5,559 abwll records of 2,244 mehraban ewes. the random regression models consisted of namely, flock-year-season of lambing as fixed effect, a fixed regression to fit average trajectory of the popu...

In this paper, an iterative decoding algorithm for channels with additive linear dynamical noise is presented. The proposed algorithm is based on the tightly coupled two inference algorithms: the sum-product algorithm which infers the information symbols of an low density parity check(LDPC) code and the Kalman smoothing algorithm which infers the channel states. The linear dynamical noise are t...

Sparse additive modeling is a class of effective methods for performing high-dimensional nonparametric regression. In this work we show how shape constraints such as convexity/concavity and their extensions, can be integrated into additive models. The proposed sparse difference of convex additive models (SDCAM) can estimate most continuous functions without any a priori smoothness assumption. M...

We consider set covering problems where the underlying set system satisfies a particular replacement property w.r.t. a given partial order on the elements: Whenever a set is in the set system then a set stemming from it via the replacement of an element by a smaller element is also in the set system. Many variants of Bin Packing that have appeared in the literature are such set covering problem...

Additive Cost Register Automata (ACRA) map strings to integers using a finite set of registers that are updated using assignments of the form “x := y + c” at every step. The corresponding class of additive regular functions has multiple equivalent characterizations, appealing closure properties, and decidable analysis questions. In this paper, we define the register complexity of an additive re...

We show that computing a relative—that is, multiplicative as opposed to additive—approximate Nash equilibrium in two-player games is PPAD-complete, even for constant values of the approximation. Our result is the first constant inapproximability result for the problem, since the appearance of the original results on the complexity of the Nash equilibrium [8, 5, 7]. Moreover, it provides an appa...

We present a new regression algorithm called Additive Groves and show empirically that it is superior in performance to a number of other established regression methods. A single Grove is an additive model containing a small number of large trees. Trees added to a Grove are trained on the residual error of other trees already in the model. We begin the training process with a single small tree ...

Asymptotic properties of two time-scale stochastic approximation algorithms with constant step sizes are analyzed in this paper. The analysis is carried out for the algorithms with additive noise, as well as for the algorithms with non-additive noise. The algorithms with additive noise are considered for the case where the noise is state-dependent and admits the decomposition as a sum of a mart...