934 resultados para 280506 Coding and Information Theory


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This paper proposes a principal-agent model between banks and firms with risk and asymmetric information. A mixed form of finance to firms is assumed. The capital structure of firms is a relevant cause for the final aggregate level of investment in the economy. In the model analyzed, there may be a separating equilibrium, which is not economically efficient, because aggregate investments fall short of the first-best level. Based on European firm-level data, an empirical model is presented which validates the result of the relevance of the capital structure of firms. The relative magnitude of equity in the capital structure makes a real difference to the profits obtained by firms in the economy.

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This ALTC Teaching Fellowship aimed to establish Guiding Principles for Library and Information Science Education 2.0. The aim was achieved by (i) identifying the current and anticipated skills and knowledge required by successful library and information science (LIS) professionals in the age of web 2.0 (and beyond), (ii) establishing the current state of LIS education in Australia in supporting the development of librarian 2.0, and in doing so, identify models of best practice. The fellowship has contributed to curriculum renewal in the LIS profession. It has helped to ensure that LIS education in Australia continues to meet the changing skills and knowledge requirements of the profession it supports. It has also provided a vehicle through which LIS professionals and LIS educators may find opportunities for greater collaboration and more open communication. This will help bridge the gap between LIS theory and practice and will foster more authentic engagement between LIS education and other parts of the LIS industry in the education of the next generation of professionals. Through this fellowship the LIS discipline has become a role model for other disciplines who will be facing similar issues in the coming years. Eighty-one members of the Australian LIS profession participated in a series of focus groups exploring the current and anticipated skills and knowledge needed by the LIS professional in the web 2.0 world and beyond. Whilst each focus group tended to draw on specific themes of interest to that particular group of people, there was a great deal of common ground. Eight key themes emerged: technology, learning and education, research or evidence-based practice, communication, collaboration and team work, user focus, business savvy and personal traits. It was acknowledged that the need for successful LIS professionals to possess transferable skills and interpersonal attributes was not new. It was noted however that the speed with which things are changing in the web 2.0 world was having a significant impact and that this faster pace is placing a new and unexpected emphasis on the transferable skills and knowledge. It was also acknowledged that all librarians need to possess these skills, knowledge and attributes and not just the one or two role models who lead the way. The most interesting finding however was that web 2.0, library 2.0 and librarian 2.0 represented a ‘watershed’ for the LIS profession. Almost all the focus groups spoke about how they are seeing and experiencing a culture change in the profession. Librarian 2.0 requires a ‘different mindset or attitude’. The Levels of Perspective model by Daniel Kim provides one lens by which to view this finding. The focus group findings suggest that we are witnessing a re-awaking of the Australian LIS profession as it begins to move towards the higher levels of Kim’s model (ie mental models, vision). Thirty-six LIS educators participated in telephone interviews aimed at exploring the current state of LIS education in supporting the development of librarian 2.0. Skills and knowledge of LIS professionals in a web 2.0 world that were identified and discussed by the LIS educators mirrored those highlighted in the focus group discussions with LIS professionals. Similarly it was noted that librarian 2.0 needed a focus less on skills and knowledge and more on attitude. However, whilst LIS professionals felt that there was a paradigm shift within the profession. LIS educators did not speak with one voice on this matter with quite a number of the educators suggesting that this might be ‘overstating it a bit’. This study provides evidence for “disparate viewpoints” (Hallam, 2007) between LIS educators and LIS professionals that can have a significant implications for the future of not just LIS professional education specifically but for the profession generally. Library and information science education 2.0: guiding principles and models of best practice 1 Inviting the LIS academics to discuss how their teaching and learning activities support the development of librarian 2.0 was a core part of the interviews conducted. The strategies used and the challenges faced by LIS educators in developing their teaching and learning approaches to support the formation of librarian 2.0 are identified and discussed. A core part of the fellowship was the identification of best practice examples on how LIS educators were developing librarian 2.0. Twelve best practice examples were identified. Each educator was recorded discussing his or her approach to teaching and learning. Videos of these interviews are available via the Fellowship blog at .The LIS educators involved in making the videos felt uncomfortable with the term ‘best practice’. Many acknowledged that there simply seeking to do the best by their students and that there was always room for improvement. For this reason these videos are offered as examples of “great practice”. The videos are a tool for other educators to use, regardless of discipline, in developing their teaching and learning approaches to supporting web 2.0 professionals. It has been argued that the main purpose of professional education is transformation (Dall’ Alba, 2009; Dall’Alba & Barnacle, 2007). As such professional education should focus not just on skills and knowledge acquisition but also on helping students to develop ways of being the professionals in question (ie LIS professionals, teachers, lawyers, engineers).The aim of this fellowship was to establish Guidelines for Library and Information Science Education 2.0 it has however become apparent that at this point in time it is not yet possible to fulfil this aim. The fellowship has clearly identified skills and knowledge needed by the LIS professional in web 2.0 world (and beyond). It has also identified examples of ‘great practice’ by LIS educators as they endeavour to develop LIS professionals who will be successful in a web 20 world. The fellowship however has also shown that the LIS profession is currently undergoing significant attitudinal and conceptual change. Consequently, before a philosophy of LIS education 2.0 can be expressed, the Australian LIS profession must first explore and articulate what it means to be an LIS professional in the 21st century (ie a world of web 2.0 and beyond). In short, the LIS profession in Australia must take stock not of “what we know and can do” but on “who we are becoming” (Dall’Alba, 2009, p 34).

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For millennia humans have sought, organized, and used information as they learned and evolved patterns of human information behaviors to resolve their human problems and survive. However, despite the current focus on living in an "information age," we have a limited evolutionary understanding of human information behavior. In this article the authors examine the current three interdisciplinary approaches to conceptualizing how humans have sought information including (a) the everyday life information seeking-sense-making approach, (b) the information foraging approach, and (c) the problem-solution perspective on information seeking approach. In addition, due to the lack of clarity regarding the role of information use in information behavior, a fourth information approach is provided based on a theory of information use. The use theory proposed starts from an evolutionary psychology notion that humans are able to adapt to their environment and survive because of our modular cognitive architecture. Finally, the authors begin the process of conceptualizing these diverse approaches, and the various aspects or elements of these approaches, within an integrated model with consideration of information use. An initial integrated model of these different approaches with information use is proposed.

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Phenomenography is a research approach devised to allow the investigation of varying ways in which people experience aspects of their world. Whilst growing attention is being paid to interpretative research in LIS, it is not always clear how the outcomes of such research can be used in practice. This article explores the potential contribution of phenomenography in advancing the application of phenomenological and hermeneutic frameworks to LIS theory, research and practice. In phenomenography we find a research toll which in revealing variation, uncovers everyday understandings of phenomena and provides outcomes which are readily applicable to professional practice. THe outcomes may be used in human computer interface design, enhancement, implementation and training, in the design and evaluation of services, and in education and training for both end users and information professionals. A proposed research territory for phenomenography in LIS includes investigating qualitative variation in the experienced meaning of: 1) information and its role in society 2) LIS concepts and principles 3) LIS processes and; 4) LIS elements.

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We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or $J$-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the $J$-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

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The literature around Library 2.0 remains largely theoretical with few empirical studies and is particularly limited in developing countries such as Indonesia. This study addresses this gap and aims to provide information about the current state of knowledge on Indonesian LIS professionals’ understanding of Library 2.0. The researchers used qualitative and quantitative approaches for this study, asking thirteen closed- and open-ended questions in an online survey. The researchers used descriptive and in vivo coding to analyze the responses. Through their analysis, they identified three themes: technology, interactivity, and awareness of Library 2.0. Respondents demonstrated awareness of Library 2.0 and a basic understanding of the roles of interactivity and technology in libraries. However, overreliance on technology used in libraries to conceptualize Library 2.0 without an emphasis on its core characteristics and principles could lead to the misalignment of limited resources. The study results will potentially strengthen the research base for Library 2.0 practice as well as inform LIS curriculum in Indonesia so as to develop practitioners who are able to adapt to users’ changing needs and expectations. It is expected that the preliminary data from this study could be used to design a much larger and more complex future research project in this area.

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In this Thesis, we develop theory and methods for computational data analysis. The problems in data analysis are approached from three perspectives: statistical learning theory, the Bayesian framework, and the information-theoretic minimum description length (MDL) principle. Contributions in statistical learning theory address the possibility of generalization to unseen cases, and regression analysis with partially observed data with an application to mobile device positioning. In the second part of the Thesis, we discuss so called Bayesian network classifiers, and show that they are closely related to logistic regression models. In the final part, we apply the MDL principle to tracing the history of old manuscripts, and to noise reduction in digital signals.

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A balance between excitatory and inhibitory synaptic currents is thought to be important for several aspects of information processing in cortical neurons in vivo, including gain control, bandwidth and receptive field structure. These factors will affect the firing rate of cortical neurons and their reliability, with consequences for their information coding and energy consumption. Yet how balanced synaptic currents contribute to the coding efficiency and energy efficiency of cortical neurons remains unclear. We used single compartment computational models with stochastic voltage-gated ion channels to determine whether synaptic regimes that produce balanced excitatory and inhibitory currents have specific advantages over other input regimes. Specifically, we compared models with only excitatory synaptic inputs to those with equal excitatory and inhibitory conductances, and stronger inhibitory than excitatory conductances (i.e. approximately balanced synaptic currents). Using these models, we show that balanced synaptic currents evoke fewer spikes per second than excitatory inputs alone or equal excitatory and inhibitory conductances. However, spikes evoked by balanced synaptic inputs are more informative (bits/spike), so that spike trains evoked by all three regimes have similar information rates (bits/s). Consequently, because spikes dominate the energy consumption of our computational models, approximately balanced synaptic currents are also more energy efficient than other synaptic regimes. Thus, by producing fewer, more informative spikes approximately balanced synaptic currents in cortical neurons can promote both coding efficiency and energy efficiency.

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Signal processing techniques play important roles in the design of digital communication systems. These include information manipulation, transmitter signal processing, channel estimation, channel equalization and receiver signal processing. By interacting with communication theory and system implementing technologies, signal processing specialists develop efficient schemes for various communication problems by wisely exploiting various mathematical tools such as analysis, probability theory, matrix theory, optimization theory, and many others. In recent years, researchers realized that multiple-input multiple-output (MIMO) channel models are applicable to a wide range of different physical communications channels. Using the elegant matrix-vector notations, many MIMO transceiver (including the precoder and equalizer) design problems can be solved by matrix and optimization theory. Furthermore, the researchers showed that the majorization theory and matrix decompositions, such as singular value decomposition (SVD), geometric mean decomposition (GMD) and generalized triangular decomposition (GTD), provide unified frameworks for solving many of the point-to-point MIMO transceiver design problems.

In this thesis, we consider the transceiver design problems for linear time invariant (LTI) flat MIMO channels, linear time-varying narrowband MIMO channels, flat MIMO broadcast channels, and doubly selective scalar channels. Additionally, the channel estimation problem is also considered. The main contributions of this dissertation are the development of new matrix decompositions, and the uses of the matrix decompositions and majorization theory toward the practical transmit-receive scheme designs for transceiver optimization problems. Elegant solutions are obtained, novel transceiver structures are developed, ingenious algorithms are proposed, and performance analyses are derived.

The first part of the thesis focuses on transceiver design with LTI flat MIMO channels. We propose a novel matrix decomposition which decomposes a complex matrix as a product of several sets of semi-unitary matrices and upper triangular matrices in an iterative manner. The complexity of the new decomposition, generalized geometric mean decomposition (GGMD), is always less than or equal to that of geometric mean decomposition (GMD). The optimal GGMD parameters which yield the minimal complexity are derived. Based on the channel state information (CSI) at both the transmitter (CSIT) and receiver (CSIR), GGMD is used to design a butterfly structured decision feedback equalizer (DFE) MIMO transceiver which achieves the minimum average mean square error (MSE) under the total transmit power constraint. A novel iterative receiving detection algorithm for the specific receiver is also proposed. For the application to cyclic prefix (CP) systems in which the SVD of the equivalent channel matrix can be easily computed, the proposed GGMD transceiver has K/log_2(K) times complexity advantage over the GMD transceiver, where K is the number of data symbols per data block and is a power of 2. The performance analysis shows that the GGMD DFE transceiver can convert a MIMO channel into a set of parallel subchannels with the same bias and signal to interference plus noise ratios (SINRs). Hence, the average bit rate error (BER) is automatically minimized without the need for bit allocation. Moreover, the proposed transceiver can achieve the channel capacity simply by applying independent scalar Gaussian codes of the same rate at subchannels.

In the second part of the thesis, we focus on MIMO transceiver design for slowly time-varying MIMO channels with zero-forcing or MMSE criterion. Even though the GGMD/GMD DFE transceivers work for slowly time-varying MIMO channels by exploiting the instantaneous CSI at both ends, their performance is by no means optimal since the temporal diversity of the time-varying channels is not exploited. Based on the GTD, we develop space-time GTD (ST-GTD) for the decomposition of linear time-varying flat MIMO channels. Under the assumption that CSIT, CSIR and channel prediction are available, by using the proposed ST-GTD, we develop space-time geometric mean decomposition (ST-GMD) DFE transceivers under the zero-forcing or MMSE criterion. Under perfect channel prediction, the new system minimizes both the average MSE at the detector in each space-time (ST) block (which consists of several coherence blocks), and the average per ST-block BER in the moderate high SNR region. Moreover, the ST-GMD DFE transceiver designed under an MMSE criterion maximizes Gaussian mutual information over the equivalent channel seen by each ST-block. In general, the newly proposed transceivers perform better than the GGMD-based systems since the super-imposed temporal precoder is able to exploit the temporal diversity of time-varying channels. For practical applications, a novel ST-GTD based system which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD DFE transceiver is also proposed.

The third part of the thesis considers two quality of service (QoS) transceiver design problems for flat MIMO broadcast channels. The first one is the power minimization problem (min-power) with a total bitrate constraint and per-stream BER constraints. The second problem is the rate maximization problem (max-rate) with a total transmit power constraint and per-stream BER constraints. Exploiting a particular class of joint triangularization (JT), we are able to jointly optimize the bit allocation and the broadcast DFE transceiver for the min-power and max-rate problems. The resulting optimal designs are called the minimum power JT broadcast DFE transceiver (MPJT) and maximum rate JT broadcast DFE transceiver (MRJT), respectively. In addition to the optimal designs, two suboptimal designs based on QR decomposition are proposed. They are realizable for arbitrary number of users.

Finally, we investigate the design of a discrete Fourier transform (DFT) modulated filterbank transceiver (DFT-FBT) with LTV scalar channels. For both cases with known LTV channels and unknown wide sense stationary uncorrelated scattering (WSSUS) statistical channels, we show how to optimize the transmitting and receiving prototypes of a DFT-FBT such that the SINR at the receiver is maximized. Also, a novel pilot-aided subspace channel estimation algorithm is proposed for the orthogonal frequency division multiplexing (OFDM) systems with quasi-stationary multi-path Rayleigh fading channels. Using the concept of a difference co-array, the new technique can construct M^2 co-pilots from M physical pilot tones with alternating pilot placement. Subspace methods, such as MUSIC and ESPRIT, can be used to estimate the multipath delays and the number of identifiable paths is up to O(M^2), theoretically. With the delay information, a MMSE estimator for frequency response is derived. It is shown through simulations that the proposed method outperforms the conventional subspace channel estimator when the number of multipaths is greater than or equal to the number of physical pilots minus one.

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We formulate and interpret several multi-modal registration methods in the context of a unified statistical and information theoretic framework. A unified interpretation clarifies the implicit assumptions of each method yielding a better understanding of their relative strengths and weaknesses. Additionally, we discuss a generative statistical model from which we derive a novel analysis tool, the "auto-information function", as a means of assessing and exploiting the common spatial dependencies inherent in multi-modal imagery. We analytically derive useful properties of the "auto-information" as well as verify them empirically on multi-modal imagery. Among the useful aspects of the "auto-information function" is that it can be computed from imaging modalities independently and it allows one to decompose the search space of registration problems.

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Gatherer, D., and McEwan, N.R. (2003). Analysis of sequence periodicity in E. coli proteins: empirical investigation of the 'duplication and divergence' theory of protein evolution. Journal of Molecular Evolution 57, 149-158. RAE2008

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This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop efficient algorithms that can effectively learn Bayesian networks, requiring only polynomial numbers of conditional independence (CI) tests in typical cases. We provide precise conditions that specify when these algorithms are guaranteed to be correct as well as empirical evidence (from real world applications and simulation tests) that demonstrates that these systems work efficiently and reliably in practice.