<p> The objective of this thesis is to compute the Misadjustment of Adaptive Predictors and to implement their fixed-point design on Xilinx Vivado for a behavioral simulation of the Prediction Gain. In the first part of this thesis, the Misadjustment is mathematically calculated for Adaptive Predictors of different tap-weights. These Adaptive Predictors include Least Mean Square (LMS), Forward-Backward LMS (FBLMS), Cascaded LMS (CLMS), and Cascaded Forward-Backward LMS (CFBLMS) for 2, 4, and 6 tap-weights. In the second part of this thesis, the 6-Tap design of all the four predictors is programmed in Verilog Hardware Description Language (HDL) using MATLAB&rsquo;s HDL Coder tool and run on the Xilinx Vivado platform for comparing behavioral simulations of the Prediction Gain with that obtained on MATLAB. An alternative method for the Prediction Gain comparison is accomplished by instantiating Xilinx Analog-to-Digital Converter (XADC) block available on 7-series Field-Programmable Gate Array (FPGA) boards as a means to introduce the input signals as voltage values. </p><p> Misadjustment is determined for 2, 4, and 6 tap-weights on all four Adaptive Predictors previously mentioned for input signals such as a sinusoid of frequency 0.1Hz contaminated with White Gaussian Noise (WGN), a second-order Auto-Regressive (AR) process, and a speech signal at 8Kbps. The results in every case reveal that FBLMS and CFBLMS show better performance, in terms of Misadjustment, when compared to LMS and CLMS Adaptive Predictors, respectively. Also, irrespective of the input signals, only the 2-Tap cascaded Adaptive Predictors such as CFBLMS and CLMS exhibit lower Misadjustment than the 2-Tap non-cascaded FBLMS and LMS predictors. And, in the case of the second-order AR process input, if AR parameters are chosen so that the eigenvalue spread is sufficiently large, then the performance of 2-Tap, 4-Tap, and 6-Tap CFBLMS and CFLMS predictors have a lower Misadjustment than that of FBLMS and LMS predictors. </p><p> The Prediction Gain calculations for the speech signal input on all the four predictors reveal that the 6-Tap CFBLMS and CLMS Adaptive Predictors show much higher gains compared to 6-Tap FBLMS and LMS Adaptive Predictors. All four 6-Tap predictors, after quantization of tap-weights to reduced number of bits for a fixed-point design, are HDL programmed on Xilinx Vivado. The behavioral simulation for Prediction Gain obtained using both the methods described reveal that the result is nearly the same as the Prediction Gain value obtained using a MATLAB simulation thereby validating the fitness of the design for FPGA implementation. Also, instantiating the XADC block for introducing input voltages, rather than hardcoding input voltages as binary-coded-decimals into Testbench, gives the leeway to feed different sets of input signals directly as voltage parameters.</p>

<p> One of the major challenges faced by the blind and the visually impaired in their daily activities, is independent navigation in an urban setting. There may be protrusions, potholes, excavations, vehicles, etc. on their path. The main aim of the assistive devices is to make the visually impaired or the blind more independent and self-sufficient. White canes and guide dogs are the primitive mobility aids they use. Currently there are many Electronic Travel Aids (ETA) and Accessible Pedestrian Signals (APS) available in the market such as the smart canes, radix rotating cone, etc.</p><p> This project presents the development, hardware implementation and testing of an Electronic Travel Aid (ETA) system, which can be used by the blind or the visually impaired for independent navigation within an urban environment. The system uses nRf24L01+ radio modules to communicate information about the street grid to user. The information includes distance to the next intersection, structure of the intersection, intersection name, and pedestrian signal status. The information is received on a hand-held device and can be converted to a voice signal by a speech synthesis device.</p>

<p>The multidimensional joint distributions that represent complex systems with many</p><p>interacting elements can be computationally expensive to characterize. Methods</p><p>to overcome this problem have been introduced by a variety of scientific communities.</p><p>Here, we employ methods from statistics, information theory and statistical</p><p>physics to investigate some approximation techniques for inference over factor graphs</p><p>of spatially-coupled low density parity check (SC-LDPC) codes, estimation of the</p><p>marginals of stationary distribution in influence networks consisting of a number of</p><p>individuals with polarized beliefs, and estimation of per-node marginalized distribution</p><p>for an adoption model of polarized beliefs represented by a Hamiltonian energy</p><p>function.</p><p>The second chapter introduces a new method to compensate for the rate loss of</p><p>SC-LDPC codes with small chain lengths. Our interest in this problem is motivated</p><p>by the theoretical question of whether or not the rate loss can be eliminated by</p><p>small modications to the boundary of the protograph? We tackle this question by</p><p>attaching additional variable nodes to the check nodes at the chain boundary. Our</p><p>goal is to increase the code rate while preserving the BP threshold of the original</p><p>chain.</p><p>In the third chapter, we consider the diffusion of polarized beliefs in a social network</p><p>based on the influence of neighbors and the effect of mass media. The adoption</p><p>process is modeled by a stochastic process called the individual-based (IN-STOCH)</p><p>system and the effects of viral diffusion and media influence are treated at the individual</p><p>level. The primary difference between our model and other recent studies,</p><p>which model both interpersonal and media influence, is that we consider a third state,</p><p>called the negative state, to represent those individuals who hold positions against</p><p>the innovation in addition to the two standard states neutral (susceptible) and positive</p><p>(adoption). Also, using a mean-eld analysis, we approximate the IN-STOCH</p><p>system in the large population limit by deterministic differential equations which we</p><p>call the homogeneous mean-eld (HOM-MEAN) and the heterogeneous mean-eld</p><p>(HET-MEAN) systems for exponential and scale-free networks, respectively. Based</p><p>on the stability of equilibrium points of these dynamical systems, we derive conditions</p><p>for local and global convergence, of the fraction of negative individuals, to</p><p>zero.</p><p>The fourth chapter also focuses on the diffusion of polarized beliefs but uses a different</p><p>mathematical model for the diffusion of beliefs. In particular, the Potts model</p><p>from statistical physics is used to model the joint distribution of the individual's</p><p>states based on a Hamiltonian energy function. Although the stochastic dynamics</p><p>of this model are not completely dened by the energy function, one can choose any</p><p>Monte Carlo sampling algorithm (e.g., Metropolis-Hastings) to dene Markov-chain</p><p>dynamics. We are primarily interested in the stationary distribution of the Markov</p><p>chain, which is given by the Boltzmann distribution. The fraction of individuals in</p><p>each state at equilibrium can be estimated using both Markov-chain Monte Carlo</p><p>methods and the belief-propagation (BP) algorithm. The main benet of the Potts</p><p>model is that the BP estimates are asymptotically exact in this case.</p> / Dissertation

There is increasing interest in using commercial-off-the-shelf (COTS) electronics in radiation environments, such as robotic systems for remediation after the nuclear accident at Fukushima or in low-cost CubeSats. Commercial electronics have varying levels or robustness to radiation environments, and without extensive testing and redesign, the survivability of COTS systems in radiation environments is unknown and potentially insufficient. This work identifies characteristics of robotic commercial-off-the-shelf component degradation, primarily part-to part variability and the interactions between the degradation of multiple components. Insight into the health of a class of components, micro-controllers, was developed using timing characteristics. A framework using either continuous or discrete Bayesian networks was developed to model the degradation observed in sensors and other electronic components. The Bayesian network can be incorporated with deterministic models to produce a robust and scalable analysis methodology, granting awareness of how the system will behave in the radiation environment and providing insight into areas for improvement in the system hardware and software.

<p>Optimization of the geometry of a metallic bowtie gap at radio frequency is presented in this thesis. Since the design and fabrication of a plasmonic device (nanogap) at nanoscale is challenging, the results of this study can be used to estimate the best design parameters for nanogap structure. The geometry of the bowtie gap including gap size, tip width, metal thickness, and tip angle are investigated at macroscale to find the maximum electric field enhancement across the gap. This thesis focuses on the simulation portion of a work that consists of experimental and simulation platforms. The simulation platform is created by NEC modeling system using antenna segments. The results indicate that 90? bowtie with 0.06 ? gap size has the most |Et|2 enhancement. Different amounts of enhancement at different frequency ranges are explained by mode volume. The product of the mode volume and |Et|2 enhancement is constant for different gap structures and different frequencies.

<p> In this thesis, an Overview of the LTE Downlink Scheduling Algorithms is presented. LTE provides high data rates and is expected to be used by many users in future since it has good coverage and has access to internet through their devices. The main mechanism of this LTE network in handling the user traffic is the scheduler. A scheduler is a key functionality in which the base-station decides which user should be given resources to receive or send the information. We focused on LTE Downlink schedulers and their functionality by studying their algorithms. The users are assigned with the shared resources by the network scheduler. We considered two scheduling algorithms, Round Robin and the Best CQI. The impact of each scheduler in terms of throughput and fairness and their abilities are known. Throughput and fairness are the two performance measures in the scheduler. By studying these two schedulers, a new scheduler is proposed which is a compromise between the throughput and the fairness.</p>

Low frequency noise measurements have been widely used to investigate the nature of defects in semiconductor devices. Characterization of low frequency noise performance at different gate bias along with the temperature is very useful to study and identify the defects in the devices. In this work, the frequency, gate bias and temperature dependence of low frequency noise of three differently processed AlGaN/GaN high electron mobility transistors (HEMTs) have been evaluated. Both the frequency-dependence and gate-voltage dependence of the low frequency noise of AlGaN/GaN HEMTs are difficult to understand within the context of the popular Hooge mobility fluctuation model. Instead, the noise is consistent with a carrier-number fluctuation model that includes a non-constant defect-energy distribution Dt(Ef ). A strongly varying Dt(Ef ) in these devices is confirmed by measurements of the temperature dependence of the noise. Estimates of the effective border-trap density before and after 1.8 MeV proton irradiation are provided for both commercial and research-grade devices using a number-fluctuation model. The input-referred noise magnitude for AlGaN/GaN HEMTs decreases at biases that are significantly more positive than the threshold voltage because the gated region of the HEMT comprises a relatively small portion of the channel, and the noise is attenuated by the voltage divider formed by the gated and ungated regions of the channel.

With the development of robotic industry, subhuman robots are paid more attention. In order to meet peopleâs requirements, robots need to grasp humanâs behaviors and service human beings. Skill transfer is the core for this procedure. In this thesis, we supply a process to transfer behaviors from humans to robots or from robots to robots. The technical contributions of this procedure include: (1) two approaches to capture humanâs behavior trajectories; (2) building model to solve robotic kinematics problems; (3) applying Dynamic Movement Primitives (DMP) to achieve targets of reproducing trajectory; (4) combining DMP with Sparse Autoencoder to increase efficient of procedure. As the result, trajectories are transferred successfully from human to robot and from robot to robot. Meanwhile, performances of inverse kinematics and DMP are proved.

Surgical interventions frequently involve the use of instruments that apply heat to tissue, e.g. to seal blood vessels. Controlling the temperature elevation created by these instruments is particularly important when operating in proximity to delicate anatomy, where the buildup of temperature can cause accidental injury and lead to permanent impairment or death. This thesis explores the use of infrared (IR) camera technology to provide thermal monitoring for two specific medical applications, i.e. bone drilling and blood vessel sealing. The technical contributions of this work include: (1) the creation of a miniature thermal stereo camera system intended to provide thermal monitoring during minimally-invasive surgical procedures; (2) the development of software to acquire and visualize the video stream produced by IR thermal cameras, based on the GigE Vision interface standard.

<p> SRAM (Static Random Access Memory) and DRAM (Dynamic Random Access Memory) are two widely used memories in microprocessor as &lsquo;cache&rsquo;. The principle of storing data is different for both. However, they belong to a common family of memories called RAM (Random Access Memory). The use of a specific type of RAM depends on the requirement. The memory size, delay, power consumption, and area are the deciding factors for choosing a type of RAM.</p><p> This project report explores the design of SRAM and DRAM. The tools used include Microwind, and P-Spice A/D. The performances of SRAM and DRAM are calculated and compared on the metrics of delay, power, and area. The calculation of the parameters provides an insight of SRAM and DRAM, and it also suggests where the performances can be improved.</p>