Polynomial-time inverse computation for accumulative functions with multiple data traversals

Real-Time Accumulative Computation Motion Detectors

The neurally inspired accumulative computation (AC) method and its application to motion detection have been introduced in the past years. This paper revisits the fact that many researchers have explored the relationship between neural networks and finite state machines. Indeed, finite state machines constitute the best characterized computational model, whereas artificial neural networks have ...

Inverse nodal problem for p-Laplacian with two potential functions

In this study, inverse nodal problem is solved for the p-Laplacian operator with two potential functions. We present some asymptotic formulas which have been proved in [17,18] for the eigenvalues, nodal points and nodal lengths, provided that a potential function is unknown. Then, using the nodal points we reconstruct the potential function and its derivatives. We also introduce a solution of i...

Polynomial time quantum computation with advice

Advice is supplementary information that enhances the computational power of an underlying computation. This paper focuses on advice that is given in the form of a pure quantum state. The notion of advised quantum computation has a direct connection to non-uniform quantum circuits and tally languages. The paper examines the influence of such advice on the behaviors of an underlying polynomial-t...

Real-time motion detection by lateral inhibition in accumulative computation

Inverse DEA Model with Fuzzy Data for Output Estimation

In this paper, we show that inverse Data Envelopment Analysis (DEA) models can be used to estimate output with fuzzy data for a Decision Making Unit (DMU) when some or all inputs are increased and deficiency level of the unit remains unchanged.