5 research outputs found

    Recent Advances in Signal Processing

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    The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

    Directional edge and texture representations for image processing

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    An efficient representation for natural images is of fundamental importance in image processing and analysis. The commonly used separable transforms such as wavelets axe not best suited for images due to their inability to exploit directional regularities such as edges and oriented textural patterns; while most of the recently proposed directional schemes cannot represent these two types of features in a unified transform. This thesis focuses on the development of directional representations for images which can capture both edges and textures in a multiresolution manner. The thesis first considers the problem of extracting linear features with the multiresolution Fourier transform (MFT). Based on a previous MFT-based linear feature model, the work extends the extraction method into the situation when the image is corrupted by noise. The problem is tackled by the combination of a "Signal+Noise" frequency model, a refinement stage and a robust classification scheme. As a result, the MFT is able to perform linear feature analysis on noisy images on which previous methods failed. A new set of transforms called the multiscale polar cosine transforms (MPCT) are also proposed in order to represent textures. The MPCT can be regarded as real-valued MFT with similar basis functions of oriented sinusoids. It is shown that the transform can represent textural patches more efficiently than the conventional Fourier basis. With a directional best cosine basis, the MPCT packet (MPCPT) is shown to be an efficient representation for edges and textures, despite its high computational burden. The problem of representing edges and textures in a fixed transform with less complexity is then considered. This is achieved by applying a Gaussian frequency filter, which matches the disperson of the magnitude spectrum, on the local MFT coefficients. This is particularly effective in denoising natural images, due to its ability to preserve both types of feature. Further improvements can be made by employing the information given by the linear feature extraction process in the filter's configuration. The denoising results compare favourably against other state-of-the-art directional representations

    Data and the city – accessibility and openness. a cybersalon paper on open data

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    This paper showcases examples of bottom–up open data and smart city applications and identifies lessons for future such efforts. Examples include Changify, a neighbourhood-based platform for residents, businesses, and companies; Open Sensors, which provides APIs to help businesses, startups, and individuals develop applications for the Internet of Things; and Cybersalon’s Hackney Treasures. a location-based mobile app that uses Wikipedia entries geolocated in Hackney borough to map notable local residents. Other experiments with sensors and open data by Cybersalon members include Ilze Black and Nanda Khaorapapong's The Breather, a "breathing" balloon that uses high-end, sophisticated sensors to make air quality visible; and James Moulding's AirPublic, which measures pollution levels. Based on Cybersalon's experience to date, getting data to the people is difficult, circuitous, and slow, requiring an intricate process of leadership, public relations, and perseverance. Although there are myriad tools and initiatives, there is no one solution for the actual transfer of that data

    Proceedings of the 7th International Conference EEDAL 2013 Energy Efficiency in Domestic Appliances and Lighting

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    This book contains the papers presented at the seventh international conference on Energy Efficiency in Domestic Appliances and Lighting. EEDAL'2013 was organised in Coimbra, Portugal in September 2013. This major international conference, which was previously been staged in Florence 1997, Naples 2000, Turin 2003, London 2006, B2e0r0l9in, Copenhagen 2011 has been very successful in attracting an international community of stakeholders dealing with residential appliances, equipment, metering liagnhdti ng (including manufacturers, retailers, consumers, governments, international organisations aangde ncies, academia and experts) to discuss the progress achieved in technologies, behavioural aspects and poliacineds , the strategies that need to be implemented to further progress this important work. Potential readers who may benefit from this book include researchers, engineers, policymakers, and all those who can influence the design, selection, application, and operation of electrical appliances and lighting.JRC.F.7-Renewables and Energy Efficienc
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