This application report describes the use of Timer_A3 to decode RC5 and SIRC TV IR remote control signals. The decoder described in this report is interrupt-driven and operates a background function using specific features the Timer_A3. Only a small portion of the MSP430 CPU?s nonreal-time resources is used. Specific hardware bit-latching capabilities of the Timer_A3 module are used for real-time decoding of the IR data signal, independent
and asynchronous to the CPU. CPU activity and power consumption are kept to an absolute minimum level. The Timer_A3 decoder implementation also allows other tasks to occur simultaneously if required. The solutions provided are written specifically for MSP430x11x(1) and MSP430x12x derivatives, but can be adapted to any other MSP430 incorporating Timer_A3.
電視遙控器設計基於MSP430
When I first studied Kalman filtering, I saw many advanced signal processing submissions here at the MATLAB Central File exchange, but I didn t see a heavily commented, basic Kalman filter present to allow someone new to Kalman filters to learn about creating them. So, a year later, I ve written a very simple, heavily commented discrete filter.
To estimate the input-output mapping with inputs x
％ and outputs y generated by the following nonlinear,
％ nonstationary state space model:
％ x(t+1) = 0.5x(t) + [25x(t)]/[(1+x(t))^(2)]
％ + 8cos(1.2t) + process noise
％ y(t) = x(t)^(2) / 20 + 6 squareWave(0.05(t-1)) + 3
％ + time varying measurement noise
％ using a multi-layer perceptron (MLP) and both the EKF and
％ the hybrid importance-samping resampling (SIR) algorithm.
Analytical constant-modulus algorithm, to separate linear combinations of CM sourcesThe algorithm
is robust in the presence of noise, and is tested on measured data,
collected from an experimental set-up.
This document is intended to serve as an introduction to Wavelet processing through a set of Matlab experiments. These experiments will gives an overview of three fundamental tasks in signal and image processing : signal, denoising and compression. These scripts are selfs contents (needed additional Matlab functions can be downloaded while reading the lectures).
Each one of these five lectures should take between 1h and 2h in order to tests the various features of the scripts. One should copy/paste the provided code into a file names e.g. tp1.m, and launch the script directly from Matlab comand line > tp1 . Some of the scripts contains "holes" that you should try to fill on your own.
I also provide the complete correction of these lectures as a set of Matlab scripts, but you should try as much as possible to avoid using them.
Noncoherent receivers are attractive for pulsed UWB systems due to the implementation simplicity. To alleviate the noise effect in detecting UWB PPM signals, this letter proposes a simple yet flexible weighted noncoherent receiver structure, which adopts a square-law integrator multiplied with a window function.
Fast settling-time added to the already conflicting requirements of narrow channel spacing and
low phase noise lead to Fractional4 divider techniques for PLL synthesizers. We analyze discrete "beat-note spurious levels from arbitrary modulus divide sequences including those from classic accumulator methods.
NAME: u2440mon.c
DESC: u2440mon entry point,menu,download
HISTORY:
Mar.25.2002:purnnamu: S3C2400X profile.c is ported for S3C2410X.
Mar.27.2002:purnnamu: DMA is enabled.
Apr.01.2002:purnnamu: isDownloadReady flag is added.
Apr.10.2002:purnnamu: - Selecting menu is available in the waiting loop.
So, isDownloadReady flag gets not needed
- UART ch.1 can be selected for the console.
Aug.20.2002:purnnamu: revision number change 0.2 -> R1.1
Sep.03.2002:purnnamu: To remove the power noise in the USB signal, the unused CLKOUT0,1 is disabled.
GloptiPoly 3: moments, optimization and
semidefinite programming.
Gloptipoly 3 is intended to solve, or at least approximate, the Generalized Problem of
Moments (GPM), an infinite-dimensional optimization problem which can be viewed as
an extension of the classical problem of moments [8]. From a theoretical viewpoint, the
GPM has developments and impact in various areas of mathematics such as algebra,
Fourier analysis, functional analysis, operator theory, probability and statistics, to cite
a few. In addition, and despite a rather simple and short formulation, the GPM has a
large number of important applications in various fields such as optimization, probability,
finance, control, signal processing, chemistry, cristallography, tomography, etc. For an
account of various methodologies as well as some of potential applications, the interested
reader is referred to [1, 2] and the nice collection of papers [5].
