arXiv subjects

Tatsuya Uezu

Publications and source records attributed to Tatsuya Uezu.

8 recordsLinked to original sources

arXiv2026

Statistical mechanical evaluation of a spread-spectrum watermarking model with image restoration II AT stability of a hybrid system with message decoding and image

In the previous paper (arxiv.org/abs/1209.4772), we proposed a spread-spectrum watermarking model with image restoration based on Bayes estimation assuming several prior probabilities and adopting the Gaussian channel model to represent attacks from unauthorized users. When an image is generated from the infinite range Ising model, we analyzed the model using the statistical mechanical method, the replica method, and derived the replica symmetric (RS) solution and performed Markov chain Monte Carlo simulations. The theoretical results of the RS solution and the simulation results were in good agreement except for some range of parameters. We treated the informed case where only the original image is known and the blind case where both the original message and the original image are unknown and found that the difference between these cases was small as long as the embedding and attack rates were small. In this paper, we treat the blind case and investigate the de Almeida-Thouless (AT) stability of the RS solution and reveal that the AT stability is broken in the range of parameters where theoretical and simulation results do not agree.

cond-mat.stat-mech↗

arXiv2019

Correspondence between Phase Oscillator Network and Classical XY Model with the same random and frustrated interactions

We study correspondence between a phase oscillator network with distributed natural frequencies and a classical XY model at finite temperatures with the same random and frustrated interactions used in the Sherrington-Kirkpatrick model. We perform numerical calculations of the spin glass order parameter $q$ and the distributions of the local fields. As a result, we find that the parameter dependences of these quantities in both models agree fairly well if parameters are normalized by using the previously obtained correspondence relation between two models with the same other types of interactions. Furthermore, we numerically calculate several quantities such as the time evolution of the instantaneous local field in the phase oscillator network in order to study the roles of synchronous and asynchronous oscillators. We also study the self-consistent equation of the local fields in the oscillator network and XY model derived by the mean field approximation.

cond-mat.dis-nn↗

arXiv2012

Statistical mechanical evaluation of spread spectrum watermarking model with image restoration

In cases in which an original image is blind, a decoding method where both the image and the messages can be estimated simultaneously is desirable. We propose a spread spectrum watermarking model with image restoration based on Bayes estimation. We therefore need to assume some prior probabilities. The probability for estimating the messages is given by the uniform distribution, and the ones for the image are given by the infinite range model and 2D Ising model. Any attacks from unauthorized users can be represented by channel models. We can obtain the estimated messages and image by maximizing the posterior probability. We analyzed the performance of the proposed method by the replica method in the case of the infinite range model. We first calculated the theoretical values of the bit error rate from obtained saddle point equations and then verified them by computer simulations. For this purpose, we assumed that the image is binary and is generated from a given prior probability. We also assume that attacks can be represented by the Gaussian channel. The computer simulation retults agreed with the theoretical values. In the case of prior probability given by the 2D Ising model, in which each pixel is statically connected with four-neighbors, we evaluated the decoding performance by computer simulations, since the replica theory could not be applied. Results using the 2D Ising model showed that the proposed method with image restoration is as effective as the infinite range model for decoding messages. We compared the performances in a case in which the image was blind and one in which it was informed. The difference between these cases was small as long as the embedding and attack rates were small. This demonstrates that the proposed method with simultaneous estimation is effective as a watermarking decoder.

cond-mat.stat-mech↗

arXiv2012

Solvable model of a phase oscillator network on a circle with infinite-range Mexican-hat-type interaction

We describe a solvable model of a phase oscillator network on a circle with infinite-range Mexican-hat-type interaction. We derive self-consistent equations of the order parameters and obtain three non-trivial solutions characterized by the rotation number. We also derive relevant characteristics such as the location-dependent distributions of the resultant frequencies of desynchronized oscillators. Simulation results closely agree with the theoretical ones.

cond-mat.dis-nn↗

arXiv2006

Statistical Mechanics of Time Domain Ensemble Learning

Conventional ensemble learning combines students in the space domain. On the other hand, in this paper we combine students in the time domain and call it time domain ensemble learning. In this paper, we analyze the generalization performance of time domain ensemble learning in the framework of online learning using a statistical mechanical method. We treat a model in which both the teacher and the student are linear perceptrons with noises. Time domain ensemble learning is twice as effective as conventional space domain ensemble learning.

cond-mat.stat-mech↗

arXiv2006

Realization of features of immune response by dynamical system models and a possible mechanism of memory of antigen invasion

Among features of real immune responses which occur when antigens invade a body,there are two remarkable features. One is that the amount of antibodies produced in the secondary invasion by the same antigens is more than 10 times larger than that in the primary invasion. The other is that more effective antibodies which can neutralize the antigens more quickly are produced by somatic hypermutation during the immune response. This phenomenon is named as 'affinity maturation'. In this paper, we try to reproduce these features by dynamical system models and present possible factors to realize them. Further, we present a model in which the memory of the invasion by antigens is realized without immune memory cells.

q-bio.PE↗

arXiv2001

Response to Invasion by Antigen and Effects of Threshold in an Immune Network Dynamical System Model with a Small Number of Degrees of Freedom

We study a dynamical system model of an idiotypic immune network with a small number of degrees of freedom, mainly focusing on the effect of a threshold above which antibodies can recognise antibodies. The response of the system to invasions by antigens is investigated in the both models with and without the threshold and it turns out that the system changes in a desirable direction for moderate magnitude of perturbation. direction for moderate magnitude of perturbation. Also, the propagation of disturbance by an antigen is investigated in the system of one-dimensionally connected basic units taking the closed 3-clone system as a unit, and it is clarified that the threshold of the system has effects to enhance the stability of the network and to localise the immune response.

cond-mat↗

arXiv2000

Analysis of immune network dynamical system model with small number of degrees of freedom

We numerically study a dynamical system model of an idiotypic immune network with a small number of degrees of freedom. The model was originally introduced by Varela et.al., and describes antibodies interacting in a body in order to prepare for the invasion of external antigens. The main purpose of this paper is to investigate the direction of change in the network system when antigens invade it. We investigate three models, original model, a modified model and a modified model with a threshold of concentration over which each antibody can recognize other antibodies. In all these models, both chaotic and periodic states exist. In particular, we find peculiar states organized in the network, the clustering state.

nlin.CD↗