Abtract - We propose a new family of fi lter banks,
named NDFB, that can achieve the directional decomposition
of arbitrary N-dimensional (N ≥ 2) signals with a simple and
effi cient tree-structured construction.
Abstract - A fl exible multiscale and directional representation for images is
proposed. The scheme combines directional fi lter banks with the
Laplacian pyramid to provides a sparse representation for two-
dimensional piecewise smooth signals resembling images. The
underlying expansion is a frame and can be designed to be a
tight frame. Pyramidal directional fi lter banks provide an effective
method to implement the digital curvelet transform. The regularity
issue of the iterated fi lters in the directional fi lter bank is examined.
Title : Implementation of quadrature modulation and demodulation
Design Object : By implementing quadrature modulation and demodulation of analog signals in digital signal processing, students will have better understanding of sampling and frequency analysis of discrete-time signals.
Design Content : Make a MATLAB function which performs quadrature modulation and demodulation for a input signal with anti-aliasing filtering.
Main program running when workpiece is ready on deferent belt(deferent_ready=ture).
* Call Square_Wave subroutine to generate 0.5ms square wave on P1.2 to drive
* electromotor,then drive deferent belt step forward. When it steps to the measure
* zone, it stops to be measured. Then call A_D subroutine to transform analog
* signals to digital signals , after then call serial subroutine to transfer
* digital signals to PC. Call square wave subroutine to drive deferent belt step to
* original position waitting for defere ready flag to run the next circle.
Commercially available active noise control headphones rely on fixed analog controllers to drive "anti-noise" loudspeakers. Our design uses an adaptive controller to optimally cancel unwanted acoustic noise. This headphone would be particularly useful for workers who operate or work near heavy machinery and engines because the noise is selectively eliminated. Desired sounds, such as speech and warning signals, are left to be heard clearly. The adaptive control algorithm is implemented on a Texas Instruments (TI™ )
1
TMS320C30GEL digital signal processor (DSP), which drives a Sony CD550 headphone/microphone system. Our experiments indicate that adaptive noise control results in a dramatic improvement in performance over fixed noise control. This improvement is due to the availability of high-performance programmable DSPs and the self-optimizing and tracking
capabilities of the adaptive controller in response to the surrounding noise.
Carrier Board for Gumstix Verdex Pro.
Has 2 - 30A motor drivers for robotic loco motion
PIC micro handles motion control.
USB host signals.
USB console connector
AC97 audio CODEC
Exapnsion headers for PIC micro.
A large body of computer-aided techniques has been developed in recent years to assist
in the process of modeling, analyzing, and designing communication systems . These
computer-aided techniques fall into two categories: formula-based approaches, where the
computer is used to evaluate complex formulas, and simulation-based approaches, where the
computer is used to simulate the waveforms or signals that flow through the system. The
second approach, which involves “waveform”-level simulation (and often incorporates
analytical techniques), is the subject of this book.
Since performance evaluation and trade off studies are the central issues in the analysis
and design of communication systems, we will focus on the use of simulation for evaluating
the performance of analog and digital communication systems with the emphasis on digitalcommunication systems.
This report presents a tutorial of fundamental array processing and beamforming theory relevant to microphone array speech processing. A microphone array consists of multiple microphones placed at different spatial locations. Built upon a knowledge of sound propagation principles, the multiple inputs can be manipulated to enhance or attenuate signals emanating from particular directions. In this way, microphone arrays provide a means of enhancing a desired signal in the presence of corrupting noise sources. Moreover, this enhancement is based purely on knowledge of the source location, and so microphone array techniques are applicable to a wide variety of noise types. Microphone arrays have great potential in practical applications of speech processing, due to their ability to provide both noise robustness and hands-free signal acquisition.
