Signal Processing MATLAB Projects

Analysis of Fix‐point Aspects for Wireless Infrastructure Systems using MATLAB

A large amount of today’s telecommunication consists of mobile and short distance wireless applications, where the effect of the channel is unknown and changing over time, and thus needs to be described statistically. Therefore the received signal cannot be accurately predicted and has to be estimated. Since telecom systems are implemented in real‐time, the hardware in the receiver for estimating the sent signal can for example be based on a DSP where the statistic calculations are performed.

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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. The LiUMIMO is designed as a Software Defined Radio (SDR), only the RF front end and the data log are implemented in hardware, while all signal processing will be performed in Matlab.

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Design of a Transmitter for Ultra Wideband Radio using MATLAB

Ultra Wideband Radio (UWB) is an upcoming alternative for wireless communications. Since the Federal Communication Commission in the USA allowed UWB for unlicensed usage in April 2002, more and more companies have started developing UWB systems. The major difference with UWB compared to other RF systems is that UWB sends information with pulses instead of using a carrier wave. The technique is from the nineteenth century and was first developed by Heinrich Hertz (1857-1894), which led to transatlantic communications 1901. This Master thesis presents a proposal of a transmitter for Ultra Wideband Radio using multiple bands. The proposed transmitter is implemented on system level in Simulink, Matlab. The frequency generation in the transmitter is also implemented at component level in a 0.13 um IBM process. The thesis begins with an introduction of UWB theory and techniques.

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Odor identity influences tracking of temporally patterned plumes in Drosophila using MATLAB

Turbulent fluid landscapes impose temporal patterning upon chemical signals, and the dynamical neuronal responses to patterned input vary across the olfactory receptor repertoire in flies, moths, and locusts. Sensory transformations exhibit low pass filtering that ultimately results in perceptual fusion of temporally transient sensory signals. For example, humans perceive a sufficiently fast flickering light as continuous, but the frequency threshold at which this fusion occurs varies with wavelength. Although the summed frequency sensitivity of the fly antenna has been examined to a considerable extent, it is unknown how intermittent odor signals are integrated to influence plume tracking behavior independent of wind cues, and whether temporal fusion for behavioral tracking might vary according to the odor encountered. Here we have adopted a virtual reality flight simulator to study the dynamics of plume tracking under different experimental conditions. Flies tethered in a magnetic field actively track continuous (non-intermittent) plumes of vinegar, banana, or ethyl butyrate with equal precision. However, pulsing these plumes at varying frequency reveals that the threshold rate, above which flies track the plume as if it were continuous, is unique for each odorant tested. Thus, the capability of a fly to navigate an intermittent plume depends on the particular odorant being tracked during flight. Finally, we measured antennal field potential responses to an intermittent plume, found that receptor dynamics track the temporal pattern of the odor stimulus and therefore do not limit the observed behavioral temporal fusion limits. This study explores the flies' ability to track odor plumes that are temporally intermittent. We were surprised to find that the perceptual critical fusion limit, determined behaviorally, is strongly dependent on odor identity. Antennal field potential recordings indicate that peripheral processing of temporal cues faithfully follow rapid odor transients above the rates that can be resolved behaviorally. These results indicate that (1) higher order circuits create a perceptually continuous signal from an intermittent sensory one, and that (2) this transformation varies with odorant rather than being constrained by sensory-motor integration, thus (3) offering an entry point for examining the mechanisms of rapid olfactory decision making in an ecological context.

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Performance Assessment of a Custom, Portable, and Low-Cost Brain-Computer Interface Platform using MATLAB

Conventional brain-computer interfaces (BCIs) are often expensive, complex to operate, and lack portability, which confines their use to laboratory settings. Portable, inexpensive BCIs can mitigate these problems, but it remains unclear whether their low-cost design compromises their performance. Therefore, we developed a portable, low-cost BCI and compared its performance to that of a conventional BCI. Methods: The BCI was assembled by integrating a custom electroencephalogram (EEG) amplifier with an open-source microcontroller and a touchscreen. The function of the amplifier was first validated against a commercial bioamplifier, followed by a head-to-head comparison between the custom BCI (using four EEG channels) and a conventional 32-channel BCI. Specifically, five able-bodied subjects were cued to alternate between hand opening/closing and remaining motionless while the BCI decoded their movement state in real time and provided visual feedback through a light emitting diode. Subjects repeated the above task for a total of 10 trials, and were unaware of which system was being used. The performance in each trial was defined as the temporal correlation between the cues and the decoded states. Results: The EEG data simultaneously acquired with the custom and commercial amplifiers were visually similar and highly correlated (ρ = 0.79). The decoding performances of the custom and conventional BCIs averaged across trials and subjects were 0.70 ± 0.12 and 0.68 ± 0.10, respectively, and were not significantly different. Conclusion: The performance of our portable, low-cost BCI is comparable to that of the conventional BCIs. Significance: Platforms, such as the one developed here, are suitable for BCI applications outside of a laboratory.

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Modeling the Human Knee using Tensegrity using MATLAB

This thesis presents a preliminary investigation of using the principles of tensegrity to model the interactions that make up the human knee. The main theory behind tensegrity is to suspend compressionable members in a network for tensile members. Current robotics literature views the human knee as a revolute joint or as a ball and socket joint. Although the simplicity of this approach has significant advantages for robotic systems, this approach has significant disadvantages for biologically inspired systems (e.g., prosthetics). The current research will investigate if tensegrity based robotic design could be used for the next generation robotics and prosthetic devices.

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Rapidly Deployable Internet-of-Things Body Area Network Platform for Medical Devices using MATLAB

Biomedical devices in the past provided limited capability for the data acquisition and presented the data in the form of user interface for a care provider to observe. Now, what is required for biomedical devices has fundamentally changed. Many devices must now support secure networking and include a network of sensors to enable machine learning-based sensor fusion for accurate inference of the subject’s state. This thesis introduces an Internet-of-Things (IoT) body area network (BAN) platform for medical devices that will provide rapid development capability with the assurance of security, networking, and the ability to host computationally intensive processes that are now required by medical devices. The BAN platform consists of seven wearable sensor nodes on the chest, wrists, upper legs, and ankles. Each sensor node includes sixteen general-purpose input/output (GPIO) pins, an analog-to-digital converter (ADC), two inter-integrated circuit (I2C) controllers, a serial peripheral interface (SPI), two universal asynchronous receiver transmitters (UART), and a universal serial bus (USB) on-the-go (OTG) to interface with sensors. The platform base model includes 9 degree-of-freedom inertial measurement unit (9DOF IMU) motion sensors, an electrocardiogram (ECG) sensor, a microphone, and a heart rate sensor. With its flexible interfaces, the platform is highly customizable and more sensors can be easily added.

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Detection of Breathing and Infant Sleep Apnea using MATLAB

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.

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A Hybrid Partially Reconfigurable Overlay Supporting Just-In-Time Assembly of Custom Accelerators on FPGAs using MATLAB

The state of the art in design and development flows for FPGAs are not sufficiently mature to allow programmers to implement their applications through traditional software development flows. The stipulation of synthesis as well as the requirement of background knowledge on the FPGAs’ low-level physical hardware structure are major challenges that prevent programmers from using FPGAs. The reconfigurable computing community is seeking solutions to raise the level of design abstraction at which programmers must operate, and move the synthesis process out of the programmers’ path through the use of overlays. A recent approach, Just-In-Time Assembly (JITA), was proposed that enables hardware accelerators to be assembled at runtime, all from within a traditional software compilation flow.

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Monophonic Pitch Recognition using MATLAB

The purpose of this project is to create a system that automatically converts monophonic music into its MIDI equivalent. Automatic pitch recognition allows for numerous commercial applications, including automatic transcription and digital storage of live performances. It is also desirable to be able to take an audio signal as an input and create a MIDI equivalent score because the MIDI information can be used to replace the original audio signal sounds with any sound the user would like. For example, if a piano composition is entered into the system, the resulting MIDI out could be used to trigger guitar samples.

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An Overview of Binary Arithmetic Architectures & Their Implementation in DSP Systems using MATLAB

This project gives looks at different binary adder and multiplier architectures and how they are implemented in a DSP system as a digital filter. Testing is performed in the Digilent Nexys2 FPA board and filters are implemented using various realizations including normal direct form I and cascade direct forms I and II. Signal filtering is performed in real time at various frequencies and results are provided on an oscilloscope and with a stereo speaker.

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Scaled Synthetic Aperture Radar System Development using MATLAB

Synthetic Aperture Radar (SAR) systems generate two dimensional images of a target area using RF energy as opposed to light waves used by cameras. When cloud cover or other optical obstructions prevent camera imaging over a target area, SAR can be substituted to generate high resolution images. Linear frequency modulated signals are transmitted and received while a moving imaging platform traverses a target area to develop high resolution images through modern digital signal processing (DSP) techniques. The motivation for this joint thesis project is to design and construct a scaled SAR system to support Cal Poly radar projects. Objectives include low-cost, high resolution SAR architecture development for capturing images in desired target areas. To that end, a scaled SAR system was successfully designed, built, and tested. The current SAR system, however, does not perform azimuthal compression and range cell migration correction (image blur reduction). These functionalities can be pursued by future students joining the ongoing radar project. The SAR system includes RF modulating, demodulating, and amplifying circuitry, broadband antenna design, movement platform, LabView system control, and MATLAB signal processing. Each system block is individually described and analyzed followed by final measured data. To confirm system operation, images developed from data collected in a single target environment are presented and compared to the actual configuration.

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Subwoofer Frequency Response Optimization by Means of Active Control using MATLAB

Most subwoofer systems have difficulties producing frequencies in the low end of the hearing spectrum due to the added power requirements and instabilities. Active controls can transform the audio signal without changing physical characteristics and ultimately generating a more impressive audio system. A Linkwitz transform crossover was implemented to extend the low end frequency response of a sealed enclosure. A graphical user interface in MATLAB was written to aid in selection of components, driver and enclosure volume. The circuit board was built and integrated with a home theater system inside of a couch and tested with a Real Time Analyzer. The Linkwitz crossover was shown to extend the frequency response, transient response and improve the subwoofer system while reducing the required enclosure volume.

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Swept-Tone Evoked Otoacoustic Emissions: Stimulus Calibration and Equalization using MATLAB

Otoacoustic Emissions (OAE) are minute acoustic responses originating from the cochlea as a result of an external acoustic stimulus and are recorded using a sensitive microphone placed in the ear canal. OAEs are acquired by synchronous stimulation with an acoustic click or tone burst and recording of the post-stimulus responses. This method of acquiring OAEs is known as transient evoked otoacoustic emissions (TEAOE) and is commonly used in clinics as a screening method for hearing and cochlear functionality in infants. Recently, a novel method of acquiring OAEs utilizing a swept-tone, or chirp, as a stimulus was developed. This method used a deconvolution process to compress the swept tone response into an impulse or click-like response. Because the human ear does not hear all frequencies (pitches) at equal loudness the swept-tone stimulus was equalized in amplitude with respect to frequency. This equalized stimulus will be perceived by the ear as equally loud in all frequencies. In this study a new hearing level equalized stimulus was designed and the OAE responses were analyzed and compared to conventional click evoked OAEs. The equalized swept-tone stimulus evoked greater magnitude OAE responses when compared to the conventional methods. It was also able to evoke responses in subjects that had little TEOAEs which might fail conventional hearing screening.

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Acquisition of Otoacoustic Emissions Using Swept-Tone Techniques using MATLAB

Otoacoustic emissions (OAEs) have been under investigation since their discovery 30 years ago (Kemp, 1978). Otoacoustic emissions are quiet sounds generated within the cochlea that can be detected with a sensitive microphone placed within the ear canal. They are used clinically as a hearing screening tool but have the potential for diagnostic and monitoring purposes. For this dissertation, high-resolution instrumentation was developed for improving the acquisition of OAEs. It was shown that a high bit-depth device is required in order to simultaneously characterize the ear canal and the cochlear responses. This led to a reduction in the stimulus artifact that revealed early latency, high-frequency otoacoustic emissions.

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Research on the use of Matlab in the Modeling of 3-phase Power Systems using MATLAB

The primary aim of this research work is to build up a MATLAB based Simulation model for 3 phase symmetrical and unsymmetrical faults. This paper ways to deal with the MATLAB programming in which transmission line model is composed and different issues has been reenacted utilizing tool compartment. Fault Analysis for different sorts of faults has been done and it impacts are appeared in simulation output, for example, voltage, current, control alongside the positive, negative and zero grouping segments of voltage and current output as far as waveforms.

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Development of Automated Agricultural Process Monitoring and Control Technology in an Enclosed System using MATLAB

For proper growth of any plants various physiological and physiochemical factors are responsible like: soil moisture, atmospheric temperature, humidity, sunlight, pH of soil, nutrient and chemical balance of soil. Biologically, these parameters are in direct relation with the process of photosynthesis, which effects the total overall growth of the plant. An Attempt has been made to develop an automated system which can measure different agricultural process parameters (like temperature, soil moisture, sunlight intensity, humidity, chemical contents etc.) and control using PID controller these parameters can be remotely monitored and control. With the help of MATLAB interfaced with NI LABVIEW, virtual designs of the real time processes are simulated.

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Bird Species Identification using Signal Processing using MATLAB

The identification of bird species from their audio recorded songs are nowadays used in several important applications, such as to monitor the quality of the environment and to prevent bird-plane collisions near airports. The complete identification cycle involves the use of: (a) recording devices to acquire the songs, (b) audio processing techniques to remove the noise and to select the most representative elements of the signal, (c) feature extraction procedures to obtain relevant characteristics, and (d) decision procedures to make the identification. The decision procedures can be obtained by Machine Learning (ML) algorithms, considering the problem in a standard classification scenario. One key element is this cycle is the selection of the most relevant segments of the audio for identification purposes. In this paper we show that the use of short audio segments with high amplitude - called pulses in our work - outperforms the use of the complete audio records in the species identification task. We also show how these pulses can be automatically obtained, based on measurements performed directly on the audio signal. The employed classifiers are trained using a previously labeled database of bird songs. We use a database that contains bird song recordings from 75 species which appear in the Southern Atlantic Coast of South America. Obtained results show that the use of automatically obtained pulses and a SVM classifier produce the best results, all the necessary procedures can be installed in a dedicated hardware, allowing the construction of a specific bird identification device.

Gabor Filter Design for Fingerprint Application Using Matlab and Verilog HDL using MATLAB

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This paper demonstrates the application of Gabor Filter technique to enhance the fingerprint image. This work produces change in Gabor filter design by increasing the quality of an output which helps in higher security applications. The incoming signal in form of image pixel will be convoluted by Gabor filter to define the Edge and vale regions of fingerprint. The main characteristic of this paper is to store image pixel in memory if convolution signal is low and if the signal is high image is filtered.

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De-Noising Audio Signals Using MATLAB Wavelets Toolbox using MATLAB

Based on the fact that noise and distortion are the main factors that limit the capacity of data transmission in telecommunications and that they also affect the accuracy of the results in the signal measurement systems, whereas, modeling and removing noise and distortions are at the core of theoretical and practical considerations in communications and signal processing. Another important issue here is that, noise reduction and distortion removal are major problems in applications such as; cellular mobile communication, speech recognition, image processing, medical signal processing, radar, sonar, and any other application where the desired signals cannot be isolated from noise and distortion.

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