Abstract: The Least Mean Squares (LMS) Algorithm can be used in a range of Digital Signal Processing applications such as echo cancellation and acoustic noise reduction. This laboratory shows how to design a model of LMS Noise Cancellation using Simulink and run it on a Texas Instruments C6000 DSP.
Subject:
Mathematics and Statistics, Science and Technology
Abstract: This module introduces adaptive filters through the example of system identification using the LMS algorithm. The adaptive filter adjusts its coefficients to minimize the mean-square error between its output and that of an unknown system.
Abstract: The TI TMS320C54x microprocessor provides a number of ways to specify the location of data to be used in calculations. Immediate addressing, direct addressing, and indirect addressing are the three main types. Knowing the basic addressing modes of a mic
Abstract: The TI TMS320C54x microprocessor provides a number of ways to specify the location of data to be used in calculations. Immediate addressing, direct addressing, and indirect addressing are the three main types. Knowing the basic addressing modes of a microprocessor is important because they map directly into assembly language syntax and because the need to use a particular addressing mode often dictates which instruction one picks for a given task.
Abstract: The Audio Conference Bridge enables a voice call with multiple (n >2) attendants. The algorithm monitors the voice signals from all attendants, and creates the signals to be transmitted to the attendants. In this module the implementation of such a bridge is described, The implementation is based on the integration of user-specific driver with the Simulink environment building blocks.
Subject:
Mathematics and Statistics, Science and Technology
Abstract: You will implement three audio effects: a fixed-length delay, a variable-length delay, and a feedback-echo. All require storing many samples in external memory.
Abstract: This module gives a technical description for an audio processing daughterboard intended for use with the TMS320F2812 eZdsp kit from Spectrum Digital.
Abstract: The module will explain Autocorrelation and its function and properties. Also, examples will be provided to help you step through some of the more complicated statistical analysis.
Subject:
Mathematics and Statistics, Science and Technology
Abstract: 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.
Abstract: Java Digital Signal Processing (J-DSP) is an object-oriented visual programming tool that enables users to establish and run online signal processing simulations, and visualize Internet based interactive demos. It has been used in laboratories involving b
Abstract: Large amounts of data can be stored in external memory. The READPROG and WRITPROG macros copy data between internal memory and external memory.
Abstract: The six-channel board for the TI EVM320C54 offers two channels of input and six channels of output at a sample rate of 44.1 kHz. It can also communicate with the PC via a serial port connection. The file thru6.asm exercises these inputs and outputs.
Abstract: The core file provides two macros, READSER and WRITSER, for communicating with a PC via the serial port. One can create graphical user interfaces in MATLAB to control the DSP in real time.