Bio: Tetsuro Nishino is an academic researcher from University of Electro-Communications. The author has contributed to research in topics: Ontology (information science) & Quantum algorithm. The author has an hindex of 8, co-authored 64 publications receiving 306 citations.
Papers published on a yearly basis
TL;DR: This work constructs negation-limited inverters of size O(n log n), with depth only O(log n), and conjecture that this is optimal, and improves a technique of Valiant for constructing monotone circuits for slice functions.
Abstract: 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, $r\leq b(n)=\lceil\log_2(n+1)\rceil$. 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 $ eg x_1, \ldots, eg x_n$ is called an inverter, for which $r=\lceil\log_2(n+1)\rceil$. 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.
TL;DR: This work integrates two elemental methods—the N-gram model and Angluin’s machine learning algorithm into an ethological data mining framework 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.
Abstract: 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.
TL;DR: Computer 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, and it was suggested that NMDA channels on the Golgi cell dendrites play an important role for determining how thegranular layer works in response to external input.
Abstract: 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.
••01 Sep 2014
TL;DR: This paper proposes a plagiarism detection method which is not influenced by changing the identifier or program statement order, and explains its capabilities by comparing it to the sim plagiarism detector.
Abstract: Learning to program is an important subject in computer science courses. During programming exercises, plagiarism by copying and pasting can lead to problems for fair evaluation. Some methods of plagiarism detection are currently available, such as sim. However, because sim is easily influenced by changing the identifier or program statement order, it fails to do enough to support plagiarism detection. In this paper, we propose a plagiarism detection method which is not influenced by changing the identifier or program statement order. We also explain our method's capabilities by comparing it to the sim plagiarism detector. Furthermore, we reveal how our method successfully detects the presence of plagiarism.
TL;DR: In this article, the complexity of negation-limited circuits that compute symmetric functions has been studied and lower bounds on the size and depth of these circuits have been shown for some specific functions such as PARITYn, MODkn and MODkn.
TL;DR: In this article, a fast Fourier transform method of topography and interferometry is proposed to discriminate between elevation and depression of the object or wave-front form, which has not been possible by the fringe-contour generation techniques.
Abstract: A fast-Fourier-transform method of topography and interferometry is proposed. By computer processing of a noncontour type of fringe pattern, automatic discrimination is achieved between elevation and depression of the object or wave-front form, which has not been possible by the fringe-contour-generation techniques. The method has advantages over moire topography and conventional fringe-contour interferometry in both accuracy and sensitivity. Unlike fringe-scanning techniques, the method is easy to apply because it uses no moving components.
01 Jan 1984
06 Jan 2012
TL;DR: In this article, a comprehensive description of basic lower bound arguments, covering many of the gems of this complexity Waterloo that have been discovered over the past several decades, right up to results from the last year or two, is given.
Abstract: Boolean circuit complexity is the combinatorics of computer science and involves many intriguing problems that are easy to state and explain, even for the layman. This book is a comprehensive description of basic lower bound arguments, covering many of the gems of this complexity Waterloo that have been discovered over the past several decades, right up to results from the last year or two. Many open problems, marked as Research Problems, are mentioned along the way. The problems are mainly of combinatorial flavor but their solutions could have great consequences in circuit complexity and computer science. The book will be of interest to graduate students and researchers in the fields of computer science and discrete mathematics.
TL;DR: Although both birdsong and human language are hierarchically organized according to particular syntactic constraints, birdsong structure is best characterized as 'phonological syntax', resembling aspects of human sound structure.