為了在CDMA系統(tǒng)中更好地應(yīng)用QDPSK數(shù)字調(diào)制方式，在分析四相相對(duì)移相（QDPSK)信號(hào)調(diào)制解調(diào)原理的基礎(chǔ)上，設(shè)計(jì)了一種QDPSK調(diào)制解調(diào)電路，它包括串并轉(zhuǎn)換、差分編碼、四相載波產(chǎn)生和選相、相干解調(diào)、差分譯碼和并串轉(zhuǎn)換電路。在MAX+PLUSⅡ軟件平臺(tái)上，進(jìn)行了編譯和波形仿真。綜合后下載到復(fù)雜可編程邏輯器件EPM7128SLC84-15中，測(cè)試結(jié)果表明，調(diào)制電路能正確選相，解調(diào)電路輸出數(shù)據(jù)與QDPSK調(diào)制輸入數(shù)據(jù)完全一致，達(dá)到了預(yù)期的設(shè)計(jì)要求。
Abstract:
In order to realize the better application of digital modulation mode QDPSK in the CDMA system， a sort of QDPSK modulation-demodulation circuit was designed based on the analysis of QDPSK signal modulation-demodulation principles. It included serial/parallel conversion circuit, differential encoding circuit, four-phase carrier wave produced and phase chosen circuit, coherent demodulation circuit, difference decoding circuit and parallel/serial conversion circuit. And it was compiled and simulated on the MAX+PLUSⅡ software platform,and downloaded into the CPLD of EPM7128SLC84-15.The test result shows that the modulation circuit can exactly choose the phase，and the output data of the demodulator circuit is the same as the input data of the QDPSK modulate. The circuit achieves the prospective requirement of the design.
Logger iButton devices have gained a lot of popularity with researchers. Although free evaluation software is easy to use and welldocumented, the choices and inputs that need to be made can sometimes be challenging. This application note explains technicalterms that are common with temperature logger iButtons and how they relate to each other. Additionally, it presents an algorithm tohelp users choose the necessary input parameters, including the sample rate based on a user's needs and the available memory tostore the data.
The purpose of this computer program is to allow the user to construct, train and test differenttypes of artificial neural networks. By implementing the concepts of templates, inheritance andderived classes from C++ object oriented programming, the necessity for declaring multiple largestructures and duplicate attributes is reduced. Utilizing dynamic binding and memory allocationafforded by C++, the user can choose to develop four separate types of neural networks:
FCMDEMO displays a GUI window to let you try out various parameters
in fuzzy c-means clustering for 2-D data. You can choose the data set
and clustering number from the GUI buttons at right, and then click
"Start" to start the fuzzy clustering process.
This applet illustrates the prediction capabilities of the multi-layer perceptrons. It allows to define an input signal on which prediction will be performed. The user can choose the number of input units, hidden units and output units, as well as the delay between the input series and the predicted output series. Then it is possible to observe interesting prediction properties.
This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global search in the joint space of the parameters and number of parameters, thereby surmounting the problem of local minima. It allows the user to choose among various model selection criteria, including AIC, BIC and MDL
This a software runing on the matlab, it is used in the channel coding simulation.
It include DVB-S2 LDPC, Covolution turbo, and block turbo code, You can choose which channel coding to run.
it run the encoder and add white noise in the channel, then it run the decoder, and compute the error rate.
％ binomial.m by David Terr, Raytheon, 5-11-04, from mathworks.com
％ Given nonnegative integers n and m with m<=n, compute the
％ binomial coefficient n choose m.
LCD and Keyboard ARMulator model for the ADS Source Code
Copy the provided ARMulate folder into your ADS directory tree
at the root, for example in c:\ADSv1_1. If prompted to
overwrite files, choose Yes.
The batch file copy_console.bat will place the appropriate
files inside the \Bin directory so that they will be found by
the ARMulator. You still need to follow the instructions
under "Using the Model" to set up the configuration files.
in this paper,we show that an efficient multiscale wedgelet decomposition is possible if we carefully choose the set of possible wedgelet orientations.
