DEMO_COND demonstrates the role of the condition
number of a matrix (with respect to inversion)
in the role of linear system solving.
Matthias Heinkenschloss
Department of Computational and Applied Mathematics
Rice University
Feb 22, 2001
The Hilbert Transform is an important component in communication systems, e.g. for single sideband modulation/demodulation, amplitude and phase detection, etc. It can be formulated as filtering operation which makes it possible to approximate the Hilbert Transform with a digital filter. Due to the non-causal and infinite impulse response of that filter, it is not that easy to get a good approximation with low hardware resource usage. Therefore, different filters with different complexities have been implemented.
The detailed discussion can be found in "Digital Hilbert Transformers or FPGA-based Phase-Locked Loops" (http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4629940).
The design is fully pipelined for maximum throughput.
This project features a full-hardware sound compressor using the well known algorithm: IMA ADPCM.
The core acts as a slave WISHBONE device.
The output is perfectly compatible with any sound player with the IMA ADPCM codec (included by default in every Windows). Includes a testbench that takes an uncompressed PCM 16 bits Mono WAV file and outputs an IMA ADPCM compressed WAV file.
Compression ratio is fixed for IMA-ADPCM, being 4:1.
PLEASE NOTICE THAT THIS CORE IS LICENSED UNDER http://creativecommons.org/licenses/by-nc-sa/3.0/ (Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported). That means you may use it only for NON-COMMERCIAL purposes.
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).
The FPGA can realize a more optimized Digital controller in DC/DC Converters when compare to DSPs. In this paper, based on the FPGA platform, The theoretical analysis, characteristics, simulation and design consideration are given. The methods to implement the digital DC/DC Converters have been researched. The function module, state machine of digital DC/DC controller and high resolution DPWM with Sigma-
Delta dither has been introduced. They are verified by experiments on a 20 W, 300 KHz non-isolated synchronous buck converters.
In this paper, the feasibility of replacing a chaos source by an equivalent digital pseudo-random generator realized using Linear Feedback Shift Register (LFSR) is studied. Particular emphasis is given on the digital implementation Piece-Wise Linear Affine Maps (PWAM). As an application, an FPGA implementation of four different maps has been experimentally verified in a FM-DCSK test radio system.
Abstract—Stable direct and indirect decentralized adaptive radial basis
neural network controllers are presented for a class of interconnected
nonlinear systems. The feedback and adaptation mechanisms for each
subsystem depend only upon local measurements to provide asymptotic
tracking of a reference trajectory. Due to the functional approximation
capabilities of radial basis neural networks, the dynamics for each
subsystem are not required to be linear in a set of unknown coeffi cients
as is typically required in decentralized adaptive schemes. In addition,
each subsystem is able to adaptively compensate for disturbances and
interconnections with unknown bounds.
Topics Practices:
Programming and Numerical Methods
Practice 1: Introduction to C
Practice 2: Cycles and functions
First part cycles
Part Two: Roles
Practice 3 - Floating point arithmetic
Practice 4 - Search for roots of functions
Practice 5 - Numerical Integration
Practice 6 - Arrangements and matrices
Part One: Arrangements
Part II: Matrices
Practice 7 - Systems of linear equations
Practice 8 - Interpolation
Practice 9 - Algorithm Design Techniques