Finite-Block-Length Analysis in Classical and Quantum Information Theory

Coding technology is used in several information processing tasks. In particular, when noise during transmission disturbs communications, coding technology is employed to protect the information. However, there are two types of coding technology: coding in classical information theory and coding in quantum information theory. Although the physical media used to transmit information ultimately obey quantum mechanics, we need to choose the type of coding depending on the kind of information device, classical or quantum, that is being used. In both branches of information theory, there are many elegant theoretical results under the ideal assumption that an infinitely large system is available. In a realistic situation, we need to account for finite size effects. The present paper reviews finite size effects in classical and quantum information theory with respect to various topics, including applied aspects

Microwave Characteristics of an Independently Biased 3-stack InGaP/GaAs HBT Configuration

This paper investigates various important microwave characteristics of an independently biased 3-stack InGaP/GaAs heterojunction bipolar transistor (HBT) monolithic microwave integrated circuit (MMIC) chip at both small-signal and large-signal operation. By taking the advantage of the independently biased functionality, bias condition for individual transistor can be adjusted flexibly, resulting in the ability of independent control for both small-signal and large-signal performances. It was found that at small-signal operation stability and isolation characteristics of the proposed configuration can be significantly improved by controlling bias condition of the second-stage and the third-stage transistors while at large-signal operation its linearity and power gain can be improved through controlling the bias condition of the first-stage and the third-stage transistors. To demonstrate the benefits of using such an independently biased configuration, a measured optimum large-signal performance at an operation frequency of 1.6 GHz under an optimum bias condition for the high gain, low distortion were obtained as: PAE = 23.5 %, Pout = 12 dBm; Gain = 32.6 dB at IMD3 = -35 dBc. Moreover, to demonstrate the superior advantage of the proposed configuration, its small-signal and large-signal performance were also compared to that of a single stage common-emitter, a conventional 2-stack, an independently biased 2-stack and a conventional 3-stack configuration. The compared results showed that the independently biased 3-stack is the best candidate among the configurations for various wireless communications applications

DNN-Based Source Enhancement to Increase Objective Sound Quality Assessment Score

We propose a training method for deep neural network (DNN)-based source enhancement to increase objective sound quality assessment (OSQA) scores such as the perceptual evaluation of speech quality (PESQ). In many conventional studies, DNNs have been used as a mapping function to estimate time-frequency masks and trained to minimize an analytically tractable objective function such as the mean squared error (MSE). Since OSQA scores have been used widely for soundquality evaluation, constructing DNNs to increase OSQA scores would be better than using the minimum-MSE to create highquality output signals. However, since most OSQA scores are not analytically tractable, i.e., they are black boxes, the gradient of the objective function cannot be calculated by simply applying back-propagation. To calculate the gradient of the OSQA-based objective function, we formulated a DNN optimization scheme on the basis of black-box optimization, which is used for training a computer that plays a game. For a black-box-optimization scheme, we adopt the policy gradient method for calculating the gradient on the basis of a sampling algorithm. To simulate output signals using the sampling algorithm, DNNs are used to estimate the probability-density function of the output signals that maximize OSQA scores. The OSQA scores are calculated from the simulated output signals, and the DNNs are trained to increase the probability of generating the simulated output signals that achieve high OSQA scores. Through several experiments, we found that OSQA scores significantly increased by applying the proposed method, even though the MSE was not minimized

An approach to rollback recovery of collaborating mobile agents

Fault-tolerance is one of the main problems that must be resolved to improve the adoption of the agents' computing paradigm. In this paper, we analyse the execution model of agent platforms and the significance of the faults affecting their constituent components on the reliable execution of agent-based applications, in order to develop a pragmatic framework for agent systems fault-tolerance. The developed framework deploys a communication-pairs independent check pointing strategy to offer a low-cost, application-transparent model for reliable agent- based computing that covers all possible faults that might invalidate reliable agent execution, migration and communication and maintains the exactly-one execution property

Fault tolerant packet-switched network design and Its sensitivity

Reliability and performance for telecommunication networks have traditionally been investigated separately in spite of their close relation. A design method integrating them for a reliable packet switched network, called a proofing method, is presented. Two heuristic design approaches (max-average, max-delay-link) for optimizing network cost in the proofing method are described. To verify their effectiveness and applicability, they are compared numerically for three example network topologies. The sensitivity of these two methods is examined with respect to changes in traffic demand and in link reliability. The design sensitivity to variation of input data is examined by changing the predicted probability of link failure, and by increasing the network traffic over the predicted value. The resulting analysis shows relative insensitivity of solutions generated by the two design methods to input data</p

High capacity data embedding schemes for digital media

High capacity image data hiding methods and robust high capacity digital audio watermarking algorithms are studied in this thesis. The main results of this work are the development of novel algorithms with state-of-the-art performance, high capacity and transparency for image data hiding and robustness, high capacity and low distortion for audio watermarking.En esta tesis se estudian y proponen diversos métodos de data hiding de imágenes y watermarking de audio de alta capacidad. Los principales resultados de este trabajo consisten en la publicación de varios algoritmos novedosos con rendimiento a la altura de los mejores métodos del estado del arte, alta capacidad y transparencia, en el caso de data hiding de imágenes, y robustez, alta capacidad y baja distorsión para el watermarking de audio.En aquesta tesi s'estudien i es proposen diversos mètodes de data hiding d'imatges i watermarking d'àudio d'alta capacitat. Els resultats principals d'aquest treball consisteixen en la publicació de diversos algorismes nous amb rendiment a l'alçada dels millors mètodes de l'estat de l'art, alta capacitat i transparència, en el cas de data hiding d'imatges, i robustesa, alta capacitat i baixa distorsió per al watermarking d'àudio.Societat de la informació i el coneixemen