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Unified theory of information with applications to computing, communications, thermodynamics, and other sciences. Digital signals and streams, codes, compression, noise, and probability. Reversible and irreversible operations. Information in biological systems. Channel capacity. Maximum-entropy formalism. Thermodynamic equilibrium, temperature. The Second Law of Thermodynamics. Quantum computation. From the course home page: Course Description 6.050J / 2.110J presents the unified theory of information with applications to computing, communications, thermodynamics, and other sciences. It covers digital signals and streams, codes, compression, noise, and probability, reversible and irreversible operations, information in biological systems, channel capacity, maximum-entropy formalism, thermodynamic equilibrium, temperature, the Second Law of Thermodynamics, and quantum computation. Designed for MIT freshmen as an elective, this course has been jointly developed by MIT's Departments of Electrical Engineering and Computer Science and Mechanical Engineering. There is no known course similar to 6.050J / 2.110J offered at any other university.

The objective of the Department of the Navy award was to facilitate and stimulate new research in the area of wireless communications. The Navy support was in the form of graduate student stipends to support the dissertation research of U.S. national students in this field, especially in the area of defining innovative solutions at the physical layer (hardware). These accomplishments include: design and development of fast DSP-ASIC processors (commercial versions licensed through Philips Semiconductor); design and development of low-power DSP-ASICs; design of digital radio subsystem and validation procedures (including the HSP43211, Intersil digital down converter); extensive compute and simulation facilities including Synopsys, Altera, TI, Philips., Includes doctoral dissertation by Jonathan Mellott.

This final report covers research carried out under Contract DAAH-04-96-1-0161 for the period June 1, 1996 through September 30, 1999. Research activities are concentrated in the following areas: multidimensional digital signal processing, optical storage and information processing, and electromagnetic measurements. Individual work units involve research in multidimensional digital signal processing and modeling, stereo and multiview image processing, nonlinear systems for image and video signal processing, linear multidimensional multiresolution processing, optical devices for information processing, semiconductor quantum wave devices, electromagnetic analysis and measurements in the time and frequency domains, and far-field, compact and near-field antenna measurement facility compensation.

A signal processing system provides and processes a digital signal generated in response to an analog signal, which includes a noise component and possibly also an information component representing four mutually orthogonal items of measurement information representable as a sample point in a symbolic four-dimensional hyper spatial reference system. An information processing and decision sub-system receives said digital signal and processes it to extract the information component. A noise likelihood determination sub-system receives the digital signal and generates a random noise assessment of whether or not the digital signal comprises solely random noise, and if not, generates an assessment of degree-of-randomness. The noise likelihood determination system controls whether or not the information processing and decision sub-system is used, in response to one or both of these generated outputs. One prospective practical application of the invention is the performance of a triage function upon signals from sonar receivers aboard naval submarines, to determine suitability of the signal for feeding to a subsequent contact localization and motion analysis (CLMA) stage., Supersedes PAT-APPL-08 716 673-96, AD-D018 191

Autoregressive analysis is used in modern signal processing applications for modeling and estimation of random signals. High speed digital signal processors with advanced architecture and special digital signal processing instructions, mostly compiled in C language, can be used in these applications to achieve realtime performance. A commercially available digital signal processor has been used in this work to estimate the AR parameters and power spectral density from the given input data by using the Levinson, Burg and Schur algorithms. This work produced a library file that contains the object files of the AR parameter estimation algorithms. The time required in terms of the cycle counts to execute each algorithm is listed for different data lengths and model orders.

This report recommends a microprocessor suitable for use in all future smart weapons. To select such a microprocessor, a general knowledge of smart weapons is presented first. For a further understanding of smart weapons, the operation of a specific system, STAFF, is described. The specifications of the desired universal microprocessor are then enumerated. The currently available microprocessors are studied, compiled, and compared. Texas Instruments TMS32OC8O is recommended as the universal microprocessor for future smart weapons.