Deterministic Boolean networks have been used as models of gene regulation and other biological networks. One key element in these models is the update schedule, which indicates the order in which states are to be updated. We study the robustness of the dynamical behavior of a Boolean network with respect to different update schedules (synchronous,… (More)
We introduce universally convex, starlike and prestarlike functions in the slit domain C \ [1, ∞), and show that there exists a very close link to completely monotone sequences and Pick functions.
A multi-resolution representation through wavelet transform has proved to be beneficial for many signal processing applications. For example, Morlet wavelet has shown good performance in tasks like audio coding and image enhancement. Unfortunately, wavelet transforms are unstable when the input signal is shifted in position. Prior works formalize this… (More)
A new approach to algorithmic trading system development is presented. This approach, Kernel Price Pattern Trading (KPPT P), allows the practitioner to link the performance of a learned classifier (that predicts the occurrence of the price pattern P) to the profitability of the system. A positive definite kernel based distance that tries to capture the… (More)
In this work some preliminary numerical results obtained by large scale simulations of the sequential dynamics of a neural network model for the graph bisection problem on random geometrically connected graphs are presented. It can be concluded that the sequential dynamic is a low cost, effective and very fast local minima optimization heuristic for the… (More)
A new regression method based on the aggregating algorithm for regression (AAR) is presented. The proposal shows how ridge regression can be modified in order to reduce the number of operations by avoiding the inverse matrix calculation only considering a sliding window of the last input values. This modification allows algorithm expression in a recursive… (More)