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Create time: 2017-09-22 13:32:10

Upload log: - The objective of this lab is to learn about BPSK and QPSK by building a QPSK modulator and demodulator. Building the QPSK Modulator and demodulator.
QAM and QPSK - Quadrature Amplitude Modulator (QAM) in digital communication system, generation of Quadrature Phase Shift Keyed (QPSK or 4-PSK) signal and demodulation. Introduction: The QAM principle: The QAM modulator.
Amplitude Modulation (Baseband, Passband).zip - A key consequence of the usual double-sideband amplitude modulation (AM) is that the range of frequencies the signal spans (its spectral bandwidth) is doubled. Thus, the RF bandwidth of a signal (measured from the lowest frequency as opposed to 0 Hz) is twice its baseband bandwidth.
Optical Quadrature psk (Coherent Detection).zip - a coherent optical receiver for demodulating optical quadrature phase-shift keying (QPSK) signals. ... Third, this scheme is applicable to multilevel modulation formats such as M-array PSK and quadrature amplitude modulation (QAM). First contribution tackles the complexity of the direct detection noncoherent receiver for differentially encoded quadrature phase shift keying.
Digital Modulation Techniques Basic - The phase of the output signal gets shifted depending upon the input. These are mainly of two types, namely Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK), according to the number of phase shifts. The other one is Differential Phase Shift Keying (DPSK) which changes the phase according to the previous value.
Speech Processing Analysis - - The number of states in GMM as the generative model of the frames is obtained using k-means algorithm. This also helps to initialize the mean vector and the covariance matrix of the individual state of the GMM. The training LPC frames collected from three speech segments are subjected to PCA for dimensionality reduction and are subjected to k-means algorithm. The total number of frames is equal to the total number of vectors that are subjected to k-means clustering.
Speech Encoding - Frequency Analysis - The speech signal for the particular isolated word can be viewed as the one generated using the sequential generating probabilistic model known as hidden Markov model (HMM). Consider there are n states in the HMM. The particular isolated speech signal is divided into finite number of frames. Every frame of the speech signal is assumed to be generated from any one of the n states. Each state is modeled as the multivariate Gaussian density function with the specified mean vector and the covariance matrix. Let the speech segment for the particular isolated word is represented as vector S. The vector S is divided into finite number of frames (say M). The i th frame is represented as Si . Every frame is generated by any of the n states with the specified probability computed using the corresponding multivariate Gaussian density model.
TELE - 753 Wireless - This course provides advanced knowledge of wideband wireless communication techniques. It include the areas of diversity: Time diversity, Space diversity, Frequency TELE9753 Advanced Wireless Communications 2 diversity; Wideband CDMA systems, Wideband OFDM systems, antenna arrays, MIMO channel modeling in the angular domain and statistical models, smart antennas techniques, multiple-input/multiple-output communications systems, spatial multiplexing, space-time processing and coding; and multiuser detection and receiver designs, multiple access and interference management, opportunistic communication, multiuser water filling.
TELE - 653 Digital - e Handbook Entry Communication concepts: Fourier transforms, random signals, Transmitter and receiver filters, matched filter, Nyquist criterion. Digital Modulation schemes: M-ary ASK, QPSK, FSK, CPM, spectral analysis of modulated signals, ML and MAP detectors, signal space methods, bit error rate analysis. Digital Receivers: carrier and clock synchronisation. Information theory: entropy, channel capacity, source coding. Channel Coding: block codes, convolutional codes.
ELEC - 733 Real Time - Examines the implementation of modern control techniques and associated instrumentation, using distributed computers. Practical hardware aspects, including measurement and actuation, data conditioning, acquisition and transmission, microprocessor devices and other distributed computing components. Commercial realisations ranging from PLCs to full process control computing systems. Software: executive operating systems, concurrency, control algorithms, numerical problems, languages and development tools in the real-time context. Design of the man-machine interface using interactive computer display systems. The role of simulation and other CAD tools. Steps of engineering development from concept to commissioning. The viewpoint of industrial design is maintained throughout.
ELEC - 723 Audio - As general-purpose computers became faster, they started to take over the role of dedicated hardware for all but the most specialized and computer-intensive operations. With the fast computers and signal processors available in the digital image processing has become the most common form of image processing and generally, is used because it is not only the most versatile method, but also the cheapest.
ELEC - 722 - The aims to give the students the fundamentals of digital image processing, covering topics from the following list: image models and physical imaging systems; visual perception; rendering systems; linear filtering; linear transforms; mathematical morphology; compression; tomographic image reconstruction; inverse problems in imaging; image enhancement; edge detection; feature extraction; and geometric diffusion.
ELEC - 104 - Signal Processing is the process of measuring, manipulating or analysing information. Signals of interest include biomedical data, audio, still or moving images, radar, and even DNA. Filtering techniques can be crucial in revealing and interpreting information present in a signal. ELEC3104 Digital Signal Processing is an introductory signal processing course which takes students through the steps necessary to design and implement filters for a range of signals.

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