It is increasingly important to structure signal processing algorithms and systems to allow for trading off between the accuracy of results and the utilization of resources in their implementation. In any particular context, there are typically a variety of heuristic approaches to managing

Detection of a visual signal requires information to reach a system capable of eliciting arbitrary responses required by the experimenter. Detection latencies are reduced when subjects receive a cue that indicates where in the visual field the signal will occur. This shift in efficiency appears

Schultz, Wolfram. Predictive reward signal of dopamine neurons. is called rewards, which elicit and reinforce approach behav-J. Neurophysiol. 80: 1–27, 1998. The effects of lesions, receptor ior. The functions of rewards were developed further during blocking, electrical self-stimulation, and drugs

We describe improvements of the currently most popular method for prediction of classically secreted proteins, SignalP. SignalP consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated. Motivated by the idea

Blind signal separation (BSS) and independent component analysis (ICA) are emerging techniques of array processing and data analysis, aiming at recovering unobserved signals or `sources' from observed mixtures (typically, the output of an array of sensors), exploiting only the assumption

cultivation.of individual microbial cells without Phylogenetic identification and in situ detection

Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear

The theoretical framework presented in this article explains expert performance as the end result of individuals ' prolonged efforts to improve performance while negotiating motivational and external constraints. In most domains of expertise, individuals begin in their childhood a regimen

Orthogonal wavelet transforms have recently become a popular representation for multiscale signal and image analysis. One of the major drawbacks of these representations is their lack of translation invariance: the content of wavelet subbands is unstable under translations of the input signal

that economics is – or should be – about individual happiness. In particular, the question is how do economic growth, unemployment and inflation, as well as institutional factors such as good governance, affect individual well-being? In addition to this intrinsic interest, there are three major reasons