Discover concise Signals and Systems MATLAB Projects ideas for students
and developers.
Get practical small-scale MATLAB project suggestions, code snippets, and guidance to build
portfolio-ready projects.
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.
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.
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.
Sleep apnea is a condition where people pause while breathing in their sleep; this can be of great concern for infants and premature babies. Current monitoring systems either require physical attachment to a user or may be unreliable. This project is meant to develop a device that can accurately detect breathing through sound and issue appropriate warnings upon its cessation. The device produced is meant to be a standalone device and thus was developed as an embedded systems project on a Xilinx Spartan 6 FPGA.
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. The other method is more intelligent with respect to the processing part as it uses note detection. Note detection allows us to recognise the portions of the audio sample where we can apply Fast Fourier Transformation algorithms. So this allows us to scale down the region of analysis for efficient run time. Thus we process the data obtained from the Power Spectrum and calculate the fundamental frequency. The frequency obtained from above estimations is used to evaluate the music note names.
In today\\\'s rapidly advancing era of automation, robotics control systems are
Learn MoreThe financial sector is witnessing a technological revolution with the rise of Large Lang
Learn More“I got full marks on my MATLAB assignment! The solution was perfect and delivered well before the deadline. Highly recommended!”
“Quick delivery and excellent communication. The team really understood the problem and provided a great solution. Will use again.”
Explore how MATLAB Solutions has helped clients achieve their academic and research goals through practical, tailored assistance.
In today\\\'s rapidly advancing era of automation, robotics control systems are evolving to meet the demand for smarter, faster, and more reliable performance. Among the many innovations driving this transformation is the use of MCP (Model-based Control Paradigms)
The financial sector is witnessing a technological revolution with the rise of Large Language Models (LLMs). Traditionally used for text analysis, LLMs are now being integrated with powerful platforms like MATLAB to develop financial forecasting models