Tetsuro Nishino

On the Complexity of Negation-Limited Boolean Networks

A theorem of Markov precisely determines the number r of NEGATION gates necessary and sufficient to compute a system of boolean functions F. For a system of boolean functions on n variables,

Ethological data mining: an automata-based approach to extract behavioral units and rules

r\leq b(n)=\lceil\log_2(n+1)\rceil

Stimulus-Dependent State Transition between Synchronized Oscillation and Randomly Repetitive Burst in a Model Cerebellar Granular Layer

. We call a circuit using b(n) NEGATION gates negation-limited. We continue recent investigations into negation-limited circuit complexity, giving both upper and lower bounds. A circuit with inputs x1,..., xn and outputs

More on the complexity of negation-limited circuits

\neg x_1, \ldots, \neg x_n

Negation-limited circuit complexity of symmetric functions

is called an inverter, for which

A Reversible Automata Approach to Modeling Birdsongs

r=\lceil\log_2(n+1)\rceil

Generation of UML package diagrams based on an attribute graph grammar

. Fischer has constructed negation-limited inverters of size O(n2 log n) and depth O(log n). Recently, Tanaka and Nishino have reduced the circuit size to O(n log2 n) at the expense of increasing the depth to log2 n. We construct negation-limited inverters of size O(n log n), with depth only O(log n), and we conjecture that this is optimal. We also improve a technique of Valiant for constructing monotone circuits for slice functions (introduced by Berkowitz). Next, we introduce some lower bound techniques for negation-limited circuits. We provide a 5n+3 log(n+1)-c lower bound for the size of a negation-limited inverter. In addition, we show that for two different restricted classes of circuit, negation-limited inverters require superlinear size.

Grammatical Inference: Algorithms and Applications

We propose an efficient automata-based approach to extract behavioral units and rules from continuous sequential data of animal behavior. By introducing novel extensions, we integrate two elemental methods—the N-gram model and Angluin’s machine learning algorithm into an ethological data mining framework. This allows us to obtain the minimized automaton-representation of behavioral rules that accept (or generate) the smallest set of possible behavioral patterns from sequential data of animal behavior. With this method, we demonstrate how the ethological data mining works using real birdsong data; we use the Bengalese finch song and perform experimental evaluations of this method using artificial birdsong data generated by a computer program. These results suggest that our ethological data mining works effectively even for noisy behavioral data by appropriately setting the parameters that we introduce. In addition, we demonstrate a case study using the Bengalese finch song, showing that our method successfully grasps the core structure of the singing behavior such as loops and branches.

A Source Code Plagiarism Detecting Method Using Sequence Alignment with Abstract Syntax Tree Elements

Information processing of the cerebellar granular layer composed of granule and Golgi cells is regarded as an important first step toward the cerebellar computation. Our previous theoretical studies have shown that granule cells can exhibit random alternation between burst and silent modes, which provides a basis of population representation of the passage-of-time (POT) from the onset of external input stimuli. On the other hand, another computational study has reported that granule cells can exhibit synchronized oscillation of activity, as consistent with observed oscillation in local field potential recorded from the granular layer while animals keep still. Here we have a question of whether an identical network model can explain these distinct dynamics. In the present study, we carried out computer simulations based on a spiking network model of the granular layer varying two parameters: the strength of a current injected to granule cells and the concentration of Mg2+ which controls the conductance of NMDA channels assumed on the Golgi cell dendrites. The simulations showed that cells in the granular layer can switch activity states between synchronized oscillation and random burst-silent alternation depending on the two parameters. For higher Mg2+ concentration and a weaker injected current, granule and Golgi cells elicited spikes synchronously (synchronized oscillation state). In contrast, for lower Mg2+ concentration and a stronger injected current, those cells showed the random burst-silent alternation (POT-representing state). It is suggested that NMDA channels on the Golgi cell dendrites play an important role for determining how the granular layer works in response to external input.

A source code plagiarism detecting method using alignment with abstract syntax tree elements

A theorem of Markov precisely determines the number r of NEGATION gates necessary and sufficient to compute a system of boolean functions F. For a system of boolean functions on n variables, r ~ [logz(n + 1)1. We call a circuit using the minimum number of NEGATION gates negation-limited. We continue recent investigations into negation-limited circuit complexity, giving both upper and lower bounds. A circuit with inputs xl, . . . . Xn and outputs mzl,...,mzn is called an inven