Consider the problem of the design of a combinational circuit with A inputs and B outputs, where each of the output variables is given as a Boolean function of the input variables. Such a circuit might be part of the control unit of a digital computer, where the A inputs are the operation code of an instruction, and the B outputs are the signals which directly control the opening and closing of...

Fixed point networks are dynamic networks encoding stimuli via distinct output patterns. Although, such networks are common in neural systems, their structures are typically unknown or poorly characterized. It is thereby valuable to use a supervised approach for resolving how a network encodes inputs of interest and the superposition of those inputs from sampled multiple node time series. In th...

The neural dynamics of the nematode Caenorhabditis elegans are experimentally low-dimensional and may be understood as long-timescale transitions between multiple low-dimensional attractors. Previous modeling work has found that dynamic models of the worm's full neuronal network are capable of generating reasonable dynamic responses to certain inputs, even when all neurons are treated as identi...

Fixed-parameter algorithms and kernelization are two powerful methods to solve NP-hard problems. Yet, so far those algorithms have been largely restricted to static inputs. In this paper we provide fixed-parameter algorithms and kernelizations for fundamental NPhard problems with dynamic inputs. We consider a variety of parameterized graph and hitting set problems which are known to have f(k)n ...

In many fisheries, particularly high seas fisheries, effort is controlled primarily by scaling estimated fleet capacity to available biomass. Capacity is traditionally estimated by relating inputs to outputs, with gaps between maximum harvest and actual harvest ascribed to technical inefficiency; precaution often dictates managing for maximum technical efficiency. I demonstrate that cruise-leve...

Experimental evidence indicates that synaptic modification depends on the timing relationship between the presynaptic inputs and the output spikes that they generate. In this letter, results are presented for models of spike-timing-dependent plasticity (STDP) whose weight dynamics is determined by a stable fixed point. Four classes of STDP are identified on the basis of the time extent of their...

In deep learning models, the inputs to network are processed using activation functions generate output corresponding these inputs. Deep models of particular importance in analyzing big data with numerous parameters and forecasting useful for image processing, natural language object recognition, financial forecasting. Also, algorithms, have been developed by taking into account features such a...

The problem of nonprehensile manipulation a stick in three-dimensional space using intermittent impulsive forces is considered. objective to juggle the between sequence configurations that are rotationally symmetric about vertical axis. dynamics described by five generalized coordinates and three control inputs. Between two consecutive where inputs applied, conveniently represented Poincaré map...

When conflicts occur during integration of visual and auditory information, one modality often dominates the other, but the underlying neural circuit mechanism remains unclear. Using auditory-visual discrimination tasks for head-fixed mice, we found that audition dominates vision in a process mediated by interaction between inputs from the primary visual (VC) and auditory (AC) cortices in the p...

We consider discrete-time plants that interact with their controllers via fixed discrete alphabet sets, and that are not subject to exogenous inputs. For this class of systems, we propose a general procedure for constructing (finite state) ⇢/μ approximations from input-output signals.