Study of sequential decoding

Decoding algorithms for data reduction and transmission through noisy space channels using sequential and hybrid computer

Objects extraction and recognition for camera-based interaction : heuristic and statistical approaches

In this thesis, heuristic and probabilistic methods are applied to a number of problems for camera-based interactions. The goal is to provide solutions for a vision based system that is able to extract and analyze interested objects in camera images and to use that information for various interactions for mobile usage. New methods and new attempts of combination of existing methods are developed for different applications, including text extraction from complex scene images, bar code reading performed by camera phones, and face/facial feature detection and facial expression manipulation. The application-driven problems of camera-based interaction can not be modeled by a uniform and straightforward model that has very strong simplifications of reality. The solutions we learned to be efficient were to apply heuristic but easy of implementation approaches at first to reduce the complexity of the problems and search for possible means, then use developed statistical learning approaches to deal with the remaining difficult but well-defined problems and get much better accuracy. The process can be evolved in some or all of the stages, and the combination of the approaches is problem-dependent. Contribution of this thesis resides in two aspects: firstly, new features and approaches are proposed either as heuristics or statistical means for concrete applications; secondly engineering design combining seveal methods for system optimization is studied. Geometrical characteristics and the alignment of text, texture features of bar codes, and structures of faces can all be extracted as heuristics for object extraction and further recognition. The boosting algorithm is one of the proper choices to perform probabilistic learning and to achieve desired accuracy. New feature selection techniques are proposed for constructing the weak learner and applying the boosting output in concrete applications. Subspace methods such as manifold learning algorithms are introduced and tailored for facial expression analysis and synthesis. A modified generalized learning vector quantization method is proposed to deal with the blurring of bar code images. Efficient implementations that combine the approaches in a rational joint point are presented and the results are illustrated.reviewe

Activity recognition using a supervised non-parametric hierarchical HMM

The problem of classifying human activities occurring in depth image sequences is addressed. The 3D joint positions of a human skeleton and the local depth image pattern around these joint positions define the features. A two level hierarchical Hidden Markov Model (H-HMM), with independent Markov chains for the joint positions and depth image pattern, is used to model the features. The states corresponding to the H-HMM bottom level characterize the granular poses while the top level characterizes the coarser actions associated with the activities. Further, the H-HMM is based on a Hierarchical Dirichlet Process (HDP), and is fully non-parametric with the number of pose and action states inferred automatically from data. This is a significant advantage over classical HMM and its extensions. In order to perform classification, the relationships between the actions and the activity labels are captured using multinomial logistic regression. The proposed inference procedure ensures alignment of actions from activities with similar labels. Our construction enables information sharing, allows incorporation of unlabelled examples and provides a flexible factorized representation to include multiple data channels. Experiments with multiple real world datasets show the efficacy of our classification approach

Wideband CMOS Data Converters for Linear and Efficient mmWave Transmitters

With continuously increasing demands for wireless connectivity, higher\ua0carrier frequencies and wider bandwidths are explored. To overcome a limited transmit power at these higher carrier frequencies, multiple\ua0input multiple output (MIMO) systems, with a large number of transmitters\ua0and antennas, are used to direct the transmitted power towards\ua0the user. With a large transmitter count, each individual transmitter\ua0needs to be small and allow for tight integration with digital circuits. In\ua0addition, modern communication standards require linear transmitters,\ua0making linearity an important factor in the transmitter design.In this thesis, radio frequency digital-to-analog converter (RF-DAC)-based transmitters are explored. They shift the transition from digital\ua0to analog closer to the antennas, performing both digital-to-analog\ua0conversion and up-conversion in a single block. To reduce the need for\ua0computationally costly digital predistortion (DPD), a linear and wellbehaved\ua0RF-DAC transfer characteristic is desirable. The combination\ua0of non-overlapping local oscillator (LO) signals and an expanding segmented\ua0non-linear RF-DAC scaling is evaluated as a way to linearize\ua0the transmitter. This linearization concept has been studied both for\ua0the linearization of the RF-DAC itself and for the joint linearization of\ua0the cascaded RF-DAC-based modulator and power amplifier (PA) combination.\ua0To adapt the linearization, observation receivers are needed.\ua0In these, high-speed analog-to-digital converters (ADCs) have a central\ua0role. A high-speed ADC has been designed and evaluated to understand\ua0how concepts used to increase the sample rate affect the dynamic performance

Submicron Systems Architecture Project: Semiannual Technical Report

No abstract available

OSO-7 Orbiting Solar Observatory program

The seventh Orbiting Solar Observatory (OSO-7) in the continuing series designed to gather solar and celestial data that cannot be obtained from the earth's surface is described. OSO-7 was launched September 29, 1971. It has been highly successful in returning scientific data giving new and important information about solar flare development, coronal temperature variations, streamer dynamics of plasma flow, and solar nuclear processes. OSO-7 is expected to have sufficient lifetime to permit data comparisons with the Skylab A mission during 1973. The OSO-7 is a second generation observatory. It is about twice as large and heavy as its predecessors, giving it considerably greater capability for scientific measurements. This report reviews mission objectives, flight history, and scientific experiments; describes the observatory; briefly compares OSO-7 with the first six OSO's; and summarizes the performance of OSO-7

Submicron Systems Architecture: Semiannual Technical Report

No abstract available