Signals and Systems MATLAB Projects

Design and Evaluation of a Discrete Wavelet Transform based Multi-Signal Receiver using MATLAB

General purpose receivers of today are designed with a broad bandwidth so that the receiver can accept a wide range of signal frequencies. These receivers usually accept one signal along with an y interference that is included. To increase the signal detection capabilities of the wide band receiver, a design for a receiver that can detect two signals is needed. One of the requirements for this receiver is that the second weak signal needs to be processed in a timely manner so that the receiver can recognize it. To remedy the problem, a module was developed using wavelet-based techniques to remove spurs from the incoming signals to allow easier detection. The main basis for this concentration on wavelets comes from the way wavelets break down signals into portions (called resolutions) that allow easier determination of detail importance.

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LiUMIMO: A MIMO Testbed for Broadband Software Defined Radio using MATLAB

In order to keep up with the increasing demand on speed and reliability in modern wireless systems, new standards have to be introduced. By using Multiple Input Multiple Output technology (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) technologies the performance can be increased dramatically. Forthcoming standards such as WLAN 802.11n, WiMax and 3GPP LTE are all taking advantage of MIMO technology. To perform realistic tests with these standards it is often not enough to run software simulations in for example Matlab. Instead, as many real world parameters as possible need to be included. This can be done using a testbed, like the LiUMIMO, that actually transmits and receives data through the air.

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Obstacle Recognition based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System using MATLAB

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions.

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MATLAB/Simulink Implementation and Analysis of Three Pulse-Width-Modulation (PWM) Techniques using MATLAB

With advances in solid-state power electronic devices and microprocessors, various pulse-width-modulation (PWM) techniques have been developed for industrial applications. For example, PWM-based three-phase voltage source inverters (VSI) convert DC power to AC power with variable voltage magnitude and variable frequency. This thesis discusses the advantages and drawbacks of three different PWM techniques: the sinusoidal PWM(SPWM) technique, the third-harmonic-injection PWM(THIPWM) technique, and the space-vector PWM (SVPWM) technique. These three methods are compared by discussing their ease of implementation and by analyzing the output harmonic spectra of various output voltages (poles voltages, line-to-neutral voltages, and line-to-line voltages) and their total harmonic distortion (THD).

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Music Note Recognition using MATLAB

The main target of the project is to get the real time estimation of the frequency of audio signal. Real time estimation will help in maintaining the data related to changes in the frequency. So we designed two different ways of estimating it. Each one has its own applications and is accurate to different types of audio.The sampling frequency is set to 44100 so that it would be compatible with all the devices.The basic approach calculates the period from the superimposition and deviation analysis of the signal.

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