An efficient reconfigurable optimal source detection and beam allocation algorithm for signal subspace factorization

Now a days, huge amount of data is communicated through channels in wireless network. It requires an efficient parallel operation for the optimal utilization of frequency, time allocation and coding model for signal subspace factorization in smart antenna. In view of this requirement, an efficient reconfigurable optimal source detection and beam allocation algorithm (RoSDBA) is proposed. The proposed algorithm is able to allocate desired signal to the user space to reduce the noise and also for efficient allocation of subspace to remove disturbance in all directions. The proposed method efficiently utilizes the antenna array elements by accurate identification and allocation of antenna array elements such as individual radiators, radiation beam, signal strength, and disturbance factor. With respect to simulation analysis, the proposed method shows better performance for the resolution, radiation beam allocations, identification bias, distribution factor and time taken for the detection of various array arrangements and source numbers

Wavefield modeling and signal processing for sensor arrays of arbitrary geometry

Sensor arrays and related signal processing methods are key technologies in many areas of engineering including wireless communication systems, radar and sonar as well as in biomedical applications. Sensor arrays are a collection of sensors that are placed at distinct locations in order to sense physical phenomena or synthesize wavefields. Spatial processing from the multichannel output of the sensor array is a typical task. Such processing is useful in areas including wireless communications, radar, surveillance and indoor positioning. In this dissertation, fundamental theory and practical methods of wavefield modeling for radio-frequency array processing applications are developed. Also, computationally-efficient high-resolution and optimal signal processing methods for sensor arrays of arbitrary geometry are proposed. Methods for taking into account array nonidealities are introduced as well. Numerical results illustrating the performance of the proposed methods are given using real-world antenna arrays. Wavefield modeling and manifold separation for vector-fields such as completely polarized electromagnetic wavefields and polarization sensitive arrays are proposed. Wavefield modeling is used for writing the array output in terms of two independent parts, namely the sampling matrix depending on the employed array including nonidealities and the coefficient vector depending on the wavefield. The superexponentially decaying property of the sampling matrix for polarization sensitive arrays is established. Two estimators of the sampling matrix from calibration measurements are proposed and their statistical properties are established. The array processing methods developed in this dissertation concentrate on polarimetric beamforming as well as on high-resolution and optimal azimuth, elevation and polarization parameter estimation. The proposed methods take into account array nonidealities such as mutual coupling, cross-polarization effects and mounting platform reflections. Computationally-efficient solutions based on polynomial rooting techniques and fast Fourier transform are achieved without restricting the proposed methods to regular array geometries. A novel expression for the Cramér-Rao bound in array processing that is tight for real-world arrays with nonidealities in the asymptotic regime is also proposed. A relationship between spherical harmonics and 2-D Fourier basis, called equivalence matrix, is established. A novel fast spherical harmonic transform is proposed, and a one-to-one mapping between spherical harmonic and 2-D Fourier spectra is found. Improvements to the minimum number of samples on the sphere that are needed in order to avoid aliasing are also proposed

Audio-visual football video analysis, from structure detection to attention analysis

Sport video is an important video genre. Content-based sports video analysis attracts great interest from both industry and academic fields. A sports video is characterised by repetitive temporal structures, relatively plain contents, and strong spatio-temporal variations, such as quick camera switches and swift local motions. It is necessary to develop specific techniques for content-based sports video analysis to utilise these characteristics. For an efficient and effective sports video analysis system, there are three fundamental questions: (1) what are key stories for sports videos; (2) what incurs viewer’s interest; and (3) how to identify game highlights. This thesis is developed around these questions. We approached these questions from two different perspectives and in turn three research contributions are presented, namely, replay detection, attack temporal structure decomposition, and attention-based highlight identification. Replay segments convey the most important contents in sports videos. It is an efficient approach to collect game highlights by detecting replay segments. However, replay is an artefact of editing, which improves with advances in video editing tools. The composition of replay is complex, which includes logo transitions, slow motions, viewpoint switches and normal speed video clips. Since logo transition clips are pervasive in game collections of FIFA World Cup 2002, FIFA World Cup 2006 and UEFA Championship 2006, we take logo transition detection as an effective replacement of replay detection. A two-pass system was developed, including a five-layer adaboost classifier and a logo template matching throughout an entire video. The five-layer adaboost utilises shot duration, average game pitch ratio, average motion, sequential colour histogram and shot frequency between two neighbouring logo transitions, to filter out logo transition candidates. Subsequently, a logo template is constructed and employed to find all transition logo sequences. The precision and recall of this system in replay detection is 100% in a five-game evaluation collection. An attack structure is a team competition for a score. Hence, this structure is a conceptually fundamental unit of a football video as well as other sports videos. We review the literature of content-based temporal structures, such as play-break structure, and develop a three-step system for automatic attack structure decomposition. Four content-based shot classes, namely, play, focus, replay and break were identified by low level visual features. A four-state hidden Markov model was trained to simulate transition processes among these shot classes. Since attack structures are the longest repetitive temporal unit in a sports video, a suffix tree is proposed to find the longest repetitive substring in the label sequence of shot class transitions. These occurrences of this substring are regarded as a kernel of an attack hidden Markov process. Therefore, the decomposition of attack structure becomes a boundary likelihood comparison between two Markov chains. Highlights are what attract notice. Attention is a psychological measurement of “notice ”. A brief survey of attention psychological background, attention estimation from vision and auditory, and multiple modality attention fusion is presented. We propose two attention models for sports video analysis, namely, the role-based attention model and the multiresolution autoregressive framework. The role-based attention model is based on the perception structure during watching video. This model removes reflection bias among modality salient signals and combines these signals by reflectors. The multiresolution autoregressive framework (MAR) treats salient signals as a group of smooth random processes, which follow a similar trend but are filled with noise. This framework tries to estimate a noise-less signal from these coarse noisy observations by a multiple resolution analysis. Related algorithms are developed, such as event segmentation on a MAR tree and real time event detection. The experiment shows that these attention-based approach can find goal events at a high precision. Moreover, results of MAR-based highlight detection on the final game of FIFA 2002 and 2006 are highly similar to professionally labelled highlights by BBC and FIFA

Subspace based carrier frequency offset estimations for OFDM systems

Master'sMASTER OF ENGINEERIN

Enabling technologies for decentralized interpersonal communication

In the recent years the Internet users have witnessed the emergence of Peer-to-Peer (P2P) technologies and applications. One class of P2P applications is comprised of applications that are targeted for interpersonal communication. The communication applications that utilize P2P technologies are referred to as decentralized interpersonal communication applications. Such applications are decentralized in a sense that they do not require assistance from centralized servers for setting up multimedia sessions between users. The invention of Distributed Hash Table (DHT) algorithms has been an important, but not an inclusive enabler for decentralized interpersonal communication. Even though the DHTs provide a basic foundation for decentralization, there are still a number of challenges without viable technological solutions. The main contribution of this thesis is to propose technological solutions to a subset of the existing challenges. In addition, this thesis also presents the preliminary work for the technological solutions. There are two parts in the preliminary work. In the first part, a set of DHT algorithms are evaluated from the viewpoint of decentralized interpersonal communication, and the second part gives a coherent presentation of the challenges that a decentralized interpersonal communication application is going to encounter in mobile networks. The technological solution proposals contain two architectures and two algorithms. The first architecture enables an interconnection between a decentralized and a centralized communication network, and the second architecture enables the decentralization of a set of legacy applications. The first algorithm is a load balancing algorithm that enables good scalability, and the second algorithm is a search algorithm that enables arbitrary searches. The algorithms can be used, for example, in DHT-based networks. Even though this thesis has focused on the decentralized interpersonal communication, some of the proposed technological solutions also have general applicability outside the scope of decentralized interpersonal communication

Enabling technologies for decentralized interpersonal communication

In the recent years the Internet users have witnessed the emergence of Peer-to-Peer (P2P) technologies and applications. One class of P2P applications is comprised of applications that are targeted for interpersonal communication. The communication applications that utilize P2P technologies are referred to as decentralized interpersonal communication applications. Such applications are decentralized in a sense that they do not require assistance from centralized servers for setting up multimedia sessions between users. The invention of Distributed Hash Table (DHT) algorithms has been an important, but not an inclusive enabler for decentralized interpersonal communication. Even though the DHTs provide a basic foundation for decentralization, there are still a number of challenges without viable technological solutions. The main contribution of this thesis is to propose technological solutions to a subset of the existing challenges. In addition, this thesis also presents the preliminary work for the technological solutions. There are two parts in the preliminary work. In the first part, a set of DHT algorithms are evaluated from the viewpoint of decentralized interpersonal communication, and the second part gives a coherent presentation of the challenges that a decentralized interpersonal communication application is going to encounter in mobile networks. The technological solution proposals contain two architectures and two algorithms. The first architecture enables an interconnection between a decentralized and a centralized communication network, and the second architecture enables the decentralization of a set of legacy applications. The first algorithm is a load balancing algorithm that enables good scalability, and the second algorithm is a search algorithm that enables arbitrary searches. The algorithms can be used, for example, in DHT-based networks. Even though this thesis has focused on the decentralized interpersonal communication, some of the proposed technological solutions also have general applicability outside the scope of decentralized interpersonal communication