A comprehensive introduction to control system synthesis in which the digital computer plays a major role, reinforced with hands-on laboratory experience. Covers elements of real-time computer architecture; input-output interfaces and data converters; analysis and synthesis of sampled-data control systems using classical and modern (state-space) methods; analysis of trade-offs in control algorithms for computation speed and quantization effects. Laboratory projects emphasize practical digital servo interfacing and implementation problems with timing, noise, nonlinear devices.

Discovering quirks in MATLAB, finding a simple noise filter, and getting great sound!

Surveys research which incorporates psychological evidence into economics. Prospect theory. Biases in probabilistic judgment. Self-control and mental accounting with implications for consumption and savings. Fairness, altruism, and public goods contributions. Financial market anomalies and theories. Impact of markets, learning, and incentives. Some evidence on memory, attention, categorization, and the thinking process.

This course covers sensing and measurement for quantitative molecular/cell/tissue analysis, in terms of genetic, biochemical, and biophysical properties. Methods include light and fluorescence microscopies; electro-mechanical probes such as atomic force microscopy, laser and magnetic traps, and MEMS devices; and the application of statistics, probability and noise analysis to experimental data.

This course presents the fundamentals of digital signal processing with particular emphasis on problems in biomedical research and clinical medicine. It covers principles and algorithms for processing both deterministic and random signals. Topics include data acquisition, imaging, filtering, coding, feature extraction, and modeling. The focus of the course is a series of labs that provide practical experience in processing physiological data, with examples from cardiology, speech processing, and medical imaging. The labs are done on the MIT Server in MATLAB® during weekly lab sessions that take place in an electronic classroom. Lectures cover signal processing topics relevant to the lab exercises, as well as background on the biological signals processed in the labs.

A series of progressive composition projects, culminating in a large final projecting, using various types of music hardware and software. Instruction in recording, editing, synthesis, sampling, digital sound processing, sequencing, and interactive systems. Close listening to computer and electronic music from various genres including Varese, Cage, Schaeffer, Xenakis, Lansky, Stockhausen, Tcherepnin, Barlow, Gunter, and Eno. Subject focuses on using the computer as a means of musical creativity and intuition.

We found that our identification system was able to tolerate an extremely high level of noise. For an SNR above 5 we were able to get the heart rate within two beats per minute one-hundred percent of the time and when it was above three we were able to identify the signal types with one-hundred percent accuracy.

" This class explores interaction with mobile computing systems and telephones by voice, including speech synthesis, recognition, digital recording, and browsing recorded speech. Emphasis on human interface design issues and interaction techniques appropriate for cognitive requirements of speech. Topics include human speech production and perception, speech recognition and text-to-speech algorithms, telephone networks, and spatial and time-compressed listening. Extensive reading from current research literature."

Introduction to microelectromechanical devices (MEMS). Material properties, microfabrication technologies, structural behavior, piezoresistive and capacitive sensing, electrostatic actuation, fluid damping, noise, amplifiers, and feedback systems. Student teams design microsystems (sensors, electronics, and feedback) to meet a set of specifications (sensitivity, frequency response, linearity) using a realistic microfabrication process. Emphasis on modeling and simulation in the design process.

Several factors of error in digital receivers are discussed.

The goal of symbol-timing recovery is to sample message signals at the receiver for best performance. After the in-phase and quadrature signals pass through a matched filter, a delay-locked loop attempts to find the peaks in the output waveforms.

After brainstorming and organizing our gameplan, we attack our problems with our method and create a MATLAB problem that gives us great distortion, according to our taste.

This course looks at the history of avant-garde and electronic music from the early twentieth century to the present. The class is organized as a theory and production seminar for which students may either produce audio/multimedia projects or a research paper. It engages music scholarship, cultural criticism, studio production, and multi-media development, such as recent software, sound design for film and games, and sound installation. Sound as a media tool for communication and sound as a form of artistic expression are subjects under discussion. The artists' work reviewed in the course includes selections from audio innovators such as the Italian Futurists, Edgard Varèse, John Cage, King Tubby, Brian Eno, Steve Reich, Afrika Bambaataa, Kraftwerk, Merzbow, Aphex Twin, Rza, Björk, and others.

Introduction to the subject of Information Communication and describes the necessity of a digital communication strategy for eliminating errors.

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.

This module describes the method of Active Noise Jamming and what happens when it is detected by a radar.

Introduction to noise and noise filtering.

This set of modules examines the mathematical analysis of noise and its effects on communications. It is a subset of a 1 semester course in communication theory.

Describes the Noisy Channel Coding Theorem.