Searcharxiv⌕ Search

arXiv subjects

Yoshihiro Yamazaki

Publications and source records attributed to Yoshihiro Yamazaki.

At least 37 records · Page 2Linked to original sources

Poincare Map Method for Limit Cycles in a Max-Plus Dynamical System

Dynamical properties of limit cycles in a two-dimensional max-plus dynamical system are discussed. We apply a Poincare map method to the limit cycles in order to reveal their stabilities. This method reduces the two dimensional system to a one-dimensional piecewise linear discrete dynamical system composed of the Poincare map and its cross section. Basins for one of the limit cycles are derived by considering the inverse system of the original model. It is found that the obtained basins show a hierarchic structure. Relationship between the Poincare map method and the method of piecewise linear mapping studied in integrable system theory for the limit cycles is discussed.

nlin.CD↗

Analysis and application of multiplicative stochastic process with a sample-dependent lower bound

A multiplicative stochastic process with the lower bound lognormally distributed is investigated. For the process, the model is constructed, and its distribution function (involving four parameters) and the related statistical properties are derived. By adjusting the parameters, it is confirmed that the theoretical distribution is consistent with empirical distributions of some real data.

physics.data-an↗

Audio Visual Scene-Aware Dialog Generation with Transformer-based Video Representations

There have been many attempts to build multimodal dialog systems that can respond to a question about given audio-visual information, and the representative task for such systems is the Audio Visual Scene-Aware Dialog (AVSD). Most conventional AVSD models adopt the Convolutional Neural Network (CNN)-based video feature extractor to understand visual information. While a CNN tends to obtain both temporally and spatially local information, global information is also crucial for boosting video understanding because AVSD requires long-term temporal visual dependency and whole visual information. In this study, we apply the Transformer-based video feature that can capture both temporally and spatially global representations more efficiently than the CNN-based feature. Our AVSD model with its Transformer-based feature attains higher objective performance scores for answer generation. In addition, our model achieves a subjective score close to that of human answers in DSTC10. We observed that the Transformer-based visual feature is beneficial for the AVSD task because our model tends to correctly answer the questions that need a temporally and spatially broad range of visual information.

cs.CL↗

Utilizing Resource-Rich Language Datasets for End-to-End Scene Text Recognition in Resource-Poor Languages

This paper presents a novel training method for end-to-end scene text recognition. End-to-end scene text recognition offers high recognition accuracy, especially when using the encoder-decoder model based on Transformer. To train a highly accurate end-to-end model, we need to prepare a large image-to-text paired dataset for the target language. However, it is difficult to collect this data, especially for resource-poor languages. To overcome this difficulty, our proposed method utilizes well-prepared large datasets in resource-rich languages such as English, to train the resource-poor encoder-decoder model. Our key idea is to build a model in which the encoder reflects knowledge of multiple languages while the decoder specializes in knowledge of just the resource-poor language. To this end, the proposed method pre-trains the encoder by using a multilingual dataset that combines the resource-poor language's dataset and the resource-rich language's dataset to learn language-invariant knowledge for scene text recognition. The proposed method also pre-trains the decoder by using the resource-poor language's dataset to make the decoder better suited to the resource-poor language. Experiments on Japanese scene text recognition using a small, publicly available dataset demonstrate the effectiveness of the proposed method.

cs.CV↗

Hierarchical Knowledge Distillation for Dialogue Sequence Labeling

This paper presents a novel knowledge distillation method for dialogue sequence labeling. Dialogue sequence labeling is a supervised learning task that estimates labels for each utterance in the target dialogue document, and is useful for many applications such as dialogue act estimation. Accurate labeling is often realized by a hierarchically-structured large model consisting of utterance-level and dialogue-level networks that capture the contexts within an utterance and between utterances, respectively. However, due to its large model size, such a model cannot be deployed on resource-constrained devices. To overcome this difficulty, we focus on knowledge distillation which trains a small model by distilling the knowledge of a large and high performance teacher model. Our key idea is to distill the knowledge while keeping the complex contexts captured by the teacher model. To this end, the proposed method, hierarchical knowledge distillation, trains the small model by distilling not only the probability distribution of the label classification, but also the knowledge of utterance-level and dialogue-level contexts trained in the teacher model by training the model to mimic the teacher model's output in each level. Experiments on dialogue act estimation and call scene segmentation demonstrate the effectiveness of the proposed method.

cs.CL↗

Koopman spectral analysis of elementary cellular automata

We perform a Koopman spectral analysis of elementary cellular automata (ECA). By lifting the system dynamics using a one-hot representation of the system state, we derive a matrix representation of the Koopman operator as a transpose of the adjacency matrix of the state-transition network. The Koopman eigenvalues are either zero or on the unit circle in the complex plane, and the associated Koopman eigenfunctions can be explicitly constructed. From the Koopman eigenvalues, we can judge the reversibility, determine the number of connected components in the state-transition network, evaluate the periods of asymptotic orbits, and derive the conserved quantities for each system. We numerically calculate the Koopman eigenvalues of all rules of ECA on a one-dimensional lattice of 13 cells with periodic boundary conditions. It is shown that the spectral properties of the Koopman operator reflect Wolfram's classification of ECA.

nlin.CG↗

Periodicity of limit cycles in a max-plus dynamical system

By introducing a max-plus dynamical system having limit cycles, we discuss their periodicity, especially the number of discrete states in them. We also find that quasi-periodic cycles exist depending on the bifurcation parameter in the system. Approximate relations between the number of states in the limit cycles and the value of the bifurcation parameter are proposed.

nlin.CD↗

Dynamical properties of max-plus equations obtained from tropically discretized Sel'kov model

Max-plus equations are derived from tropically discretized Sel'kov model via ultradiscretization. These max-plus equations possess common dynamical structures with the discretized model: Neimark-Sacker bifurcation and limit cycles. The limit cycles of the ultradiscrete max-plus equations have seven discrete states. Furthermore, these max-plus equations exhibit excitability. Relationship between the tropically discretized model and the derived max-plus equations is also discussed based on numerical results. It is found that the derived max-plus equations correspond to a limiting case of the tropically discretized model.

nlin.CD↗

A simple model for ultradiscrete Hopf bifurcation

Dynamical properties of ultradiscrete Hopf bifurcation, similar to those of the standard Hopf bifurcation, are discussed by proposing a simple model of ultradiscrete equations with max-plus algebra. In ultradiscrete Hopf bifurcation, limit cycles emerge depending on the value of a bifurcation parameter in the model. The limit cycles are composed of a finite number of discrete states. Furthermore, the model exhibits excitability. The model is derived from two different dynamical models with Hopf bifurcation by means of ultradiscretization; it is a candidate for a normal form for ultradiscrete Hopf bifurcation.

nlin.CD↗

Ultradiscrete Bifurcations for One Dimensional Dynamical Systems

Bifurcations of one dimensional dynamical systems are discussed based on some ultradiscrete equations. The ultradiscrete equations are derived from normal forms of one-dimensional nonlinear differential equations, each of which has saddle-node, transcritical, or supercritical pitchfork bifurcations. An additional bifurcation, which is similar to flip bifurcation, is found in ultradiscrete equations for supercritical pitchfork bifurcation. Dynamical properties of these ultradiscrete bifurcations can be characterized with graphical analysis. As an example of application of our treatment, we focus on an ultradiscrete equation of FitzHugh-Nagumo model, and discuss its dynamical properties.

nlin.CD↗

Space evaluation in football games via field weighting based on tracking data

In football game analysis, space evaluation is an important issue because it is directly related to the quality of ball passing or player formations. Previous studies have primarily focused on a field division approach wherein a field is divided into dominant regions in which a certain player can arrive prior to any other players. However, the field division approach is oversimplified because all locations within a region are regarded as uniform herein. The objective of the current study is to propose a fundamental framework for space evaluation based on field weighting. In particular, we employed the motion model and calculated a minimum arrival time $ τ$ for each player to all locations on the football field. Our main contribution is that two variables $ τ_{\textrm{of}} $ and $ τ_{\textrm{df}} $ corresponding to the minimum arrival time for offense and defense teams are considered; using $ τ_{\textrm{of}} $ and $ τ_{\textrm{df}} $, new orthogonal variables $ z_{1} $ and $ z_{2} $ are defined. In particular, based on real datasets comprising of data from 45 football games of the J1 League in 2018, we provide a detailed characterization of $ z_{1} $ and $ z_{2} $ in terms of ball passing. By using our method, we found that $ z_{1}(\vec{x}, t) $ and $ z_{2}(\vec{x}, t) $ represent the degree of safety for a pass made to $ \vec{x} $ at $ t $ and degree of sparsity of $ \vec{x} $ at $ t $, respectively; the success probability of passes could be well-fitted using a sigmoid function. Moreover, a new type of field division approach and evaluation of ball passing just before shoots using real game data are discussed.

physics.soc-ph↗

Lifetime distributions for adjacency relationships in a Vicsek model

We investigate the statistical properties of adjacency relationships in a two-dimensional Vicsek model. We define adjacent edges for all particles at every time step by (a) Delaunay triangulation and (b) Euclidean distance, and obtain cumulative distributions $ P(τ) $ of lifetime $ τ$ of the edges. We find that the shape of $ P(τ) $ changes from an exponential to a power law depending on the interaction radius, which is a parameter of the Vicsek model. We discuss the emergence of the power-law distribution from the viewpoint of first passage time problem for a fractional Brownian motion.

physics.soc-ph↗

Clustering algorithm for formations in football games

This paper develops a clustering algorithm for formations in team sports, with a focus on football games. Our method first clusters formations into several average formations: `442,' `4141,' `433,' `541,' and `343.' Then, each average formation is further divided into more specific patterns in which the configurations of players are slightly different. The latter step is based on hierarchical clustering and the Delaunay method, which defines the formation of a team as an adjacency matrix of Delaunay triangulation. A formation clustered using our method is expressed in a form such as `442-C1'.

physics.soc-ph↗

Universal topological representation of geometric patterns

We discuss here geometric structures of condensed matters by means of a fundamental topological method. Any geometric pattern can be universally represented by a decomposition space of a topological space consisting of the infinite product space of 0 and 1, in which a partition with a specific topological structure determines a character of each geometric structure.

math-ph↗

Characterization of the formation structure in team sports

We propose a method to identify the formation structure in team sports based on Delaunay triangulation. The adjacency matrix obtained from the Delaunay triangulation for each player is regarded as the formation pattern. Our method allows time-series analysis and a quantitative comparison of formations. A classification algorithm of formations is also proposed by combining our method with hierarchical clustering.

physics.soc-ph↗

Statistical properties for directional alignment and chasing of players in football games

Focusing on motion of two interacting players in football games, two velocity vectors for the pair of one player and the nearest opponent player exhibit strong alignment. Especially, we find that there exists a characteristic interpersonal distance $ r\simeq 500 $ cm below which the circular variance for their alignment decreases rapidly. By introducing the order parameter $ ϕ(t) $ in order to measure degree of alignment of players' velocity vectors, we also find that the angle distribution between the nearest players' velocity vectors becomes wrapped Cauchy ($ ϕ\lesssim 0.7 $) and the mixture of von Mises and wrapped Cauchy distributions ($ ϕ\gtrsim 0.7 $), respectively. To understand these findings, we construct a simple model for the motion of the two interacting players with the following rules: chasing between the players and the reset of the chasing. We numerically show that our model successfully reproduce the results obtained from the actual data. Moreover, from the numerical study, we find that there is another characteristic distance $ r\simeq 1000 $ cm below which player's chasing starts.

physics.soc-ph↗

Degree distribution of position-dependent ball-passing networks in football games

We propose a simple stochastic model describing the position-dependent ball-passing network in football games. In this network, a player on a certain area in the divided fields is a node, and a pass between two nodes corresponds to an edge. Our model is characterized by the consecutive choice of a node dependent on its intrinsic fitness. We derive the explicit expression of the degree distribution, and find that the derived distribution reproduces the real data quit well.

physics.soc-ph↗

Structure and modeling of the network of two-Chinese-character compound words in the Japanese language

This paper proposes a numerical model of the network of two-Chinese-character compound words (two-character network, for short). In this network, a Chinese character is a node and a two-Chinese-character compound word links two nodes. The basic framework of the model is that an important character gets many edges. As the importance of a character, we use the frequency of each character appearing in publications. The direction of edge is given according to a random number assigned to nodes. The network generated by the model is small-world and scale-free, and reproduces statistical properties in the actual two-character network quantitatively.

physics.soc-ph↗