The double-density DWT is an improvement upon the critically sampled DWT with important additional properties: (1) It employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half, (2) The double-density DWT is overcomplete by a factor of two, and (3) It is nearly shift-invariant. In two dimensions, this transform outperforms the standard DWT in terms of denoising however, there is room for improvement because not all of the wavelets are directional. That is, although the double-density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions.
this is a digital intercom projects using ADC PWM and UART interrupt.
you take the value from mic enter it to ADC and then send serially to the other microcontroller which receives the data and transform the digital data into analog data by PWM which is connected to speaker
NN Functions
a program in Lisp to demonstrate working of an artificial neuron. (Enter an input vector X and weight vector W. Calculate weighted sum XW. Transform this using signal or activation functions like logistic, threshold, hyperbolic-tangent, linear, exponential, sigmoid or some other functions (syntax provided) and display the output).
P3.18. An analog signal xa(t) = sin (100πt) is sampled using the following sampling intervals. In
each case plot the spectrum of the resulting discrete-time signal.
Ts= 0.1 ms, Ts= 1 ms, Ts = 0.01 Sec
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.
David Vernon is the Coordinator of the European Network for the Advancement of Artificial Cognitive Systems and he is a Visiting Professor of Cognitive Systems at the University of Genoa. He is also a member of the management team of the RobotCub integrated working on the development of open-source cognitive humanoid robot.
Over the past 27 years, he has held positions at Westinghouse Electric, Trinity College Dublin, the European Commission, the National University of Ireland Maynooth, Science Foundation Ireland, and Etisalat University College.
He has authored two and edited three books on computer vision and has published over eighty papers in the fields of Computer Vision, Robotics, and Cognitive Systems. His research interests include Fourier-based computer vision and enactive approaches to cognition.
He is currently a Professor at Etisalat University College in Sharjah-United Arab Emirates, focusing on Masters programs by research in Computing fields.".[1]
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.
