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PERCOLATION STUDY OF NANO-COMPOSITE CONDUCTIVITY USING MONTE CARLO SIMULATIONPERCOLATION
Title
PERCOLATION STUDY OF NANO-COMPOSITE CONDUCTIVITY USING MONTE CARLO SIMULATIONPERCOLATION.
Creator
Bai, Jing, Lin, Kuo-Chi, University of Central Florida
Abstract / Description
A Monte Carlo model is developed for predicting electrical conductivity of carbon nanofiber composite materials. The conductive nanofibers are models as both 2D and 3D network of finite sites that are randomly distributed. The percolation behavior of the network is studied using the Monte Carlo method, which leads to the determination of the percolation threshold. The effect of the nanofiber aspect ratio on the critical nanofiber volume rate is investigated in the current model, each of the...
Show moreA Monte Carlo model is developed for predicting electrical conductivity of carbon nanofiber composite materials. The conductive nanofibers are models as both 2D and 3D network of finite sites that are randomly distributed. The percolation behavior of the network is studied using the Monte Carlo method, which leads to the determination of the percolation threshold. The effect of the nanofiber aspect ratio on the critical nanofiber volume rate is investigated in the current model, each of the nanofibers needs five independent geometrical parameters (i.e., three coordinates in space and two orientation angles) for its identification. There are three controlling parameters for each nanofiber, which includes the nanofiber length, the nanofiber diameter, and the nanofiber aspect ratio. The simulation results reveal a relationship between the fiber aspect ratio and the percolation threshold: the higher the aspect ratio, the lower the threshold. With the simulation results obtained from the Monte Carlo model, the effective electrical conductivity of the composite is then determined by assuming the conductivity is proportional to the ratio of the number of nanofibers forming the largest cluster to the total number of nanofibers. The numerical results indicate that as the volume rate reaches a critical value, the conductivity starts to rise sharply. These obtained simulation results agree fairly with experimental and numerical data published earlier by others. In addition, we investigate the convergence of the current percolation model. We also find the tunneling effect does not affect the critical volume rate greatly. We propose that the percolation model is not scalable as well.
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Date Issued
2009
Identifier
CFE0002644, ucf:48230
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002644
STUDY OF LOW SPEED TRANSITIONAL REGIME GAS FLOWS IN MICROCHANNELS USING INFORMATION PRESERVATION (IP) METHOD
Title
STUDY OF LOW SPEED TRANSITIONAL REGIME GAS FLOWS IN MICROCHANNELS USING INFORMATION PRESERVATION (IP) METHOD.
Creator
KURSUN, Umit, Kapat, Jayanta, University of Central Florida
Abstract / Description
Proper design of thermal management solutions for future nano-scale electronics or photonics will require knowledge of flow and transport through micron-scale ducts. As in the macro-scale conventional counterparts, such micron-scale flow systems would require robust simulation tools for early-stage design iterations. It can be envisioned that an ideal Nanoscale thermal management (NSTM) solution will involve two-phase flow, liquid flow and gas flow. This study focuses on numerical simulation...
Show moreProper design of thermal management solutions for future nano-scale electronics or photonics will require knowledge of flow and transport through micron-scale ducts. As in the macro-scale conventional counterparts, such micron-scale flow systems would require robust simulation tools for early-stage design iterations. It can be envisioned that an ideal Nanoscale thermal management (NSTM) solution will involve two-phase flow, liquid flow and gas flow. This study focuses on numerical simulation gas flow in microchannels as a fundamental thermal management technique in any future NSTM solution. A well-known particle-based method, Direct Simulation Monte Carlo (DSMC) is selected as the simulation tool. Unlike continuum based equations which would fail at large Kn numbers, the DSMC method is valid in all Knudsen regimes. Due to its conceptual simplicity and flexibility, DSMC has a lot of potential and has already given satisfactory answers to a broad range of macroscopic problems. It has also a lot of potential in handling complex MEMS flow problems with ease. However, the high-level statistical noise in DSMC must be eliminated and pressure boundary conditions must be effectively implemented in order to utilize the DSMC under subsonic flow conditions. The statistical noise of classical DSMC can be eliminated trough the use of IP method. The method saves computational time by several orders of magnitude compared to a similar DSMC simulation. As in the regular DSMC procedures, the molecular velocity is used to determine the molecular positions and compute collisions. Separating the macroscopic velocity from the molecular velocity through the use of the IP method, however, eliminates the high-level of statistical noise as typical in DSMC calculations of low-speed flows. The conventional boundary conditions of the classical DSMC method, such as constant velocity free-stream and vacuum conditions are incorrect in subsonic flow conditions. There should be a substantial amount of backpressure allowing new molecules to enter from the outlet as well as inlet boundaries. Additionally, the application of pressure boundaries will facilitate comparison of numerical and experimental results more readily. Therefore, the main aim of this study is to build the unidirectional, non-isothermal IP algorithm method with periodic boundary conditions on the two dimensional classical DSMC algorithm. The IP algorithm is further modified to implement pressure boundary conditions using the method of characteristics. The applicability of the final algorithm in solving a real flow situation is verified on parallel plate Poiseuille and backward facing step flows in microchannels which are established benchmark problems in computational fluid dynamics studies. The backward facing step geometry is also of practical importance in a variety of engineering applications including Integrated Circuit (IC) design. Such an investigation in microchannels with sufficient accuracy may provide insight into the more complex flow and transport processes in any future Nanoscale thermal management (NSTM) solution. The flow and heat transfer mechanisms at different Knudsen numbers are investigated.
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Date Issued
2006
Identifier
CFE0001281, ucf:46910
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001281
MULTIPLE SCATTERING OF LIGHT IN INHOMOGENEOUS MEDIA AND APPLICATIONS
Title
MULTIPLE SCATTERING OF LIGHT IN INHOMOGENEOUS MEDIA AND APPLICATIONS.
Creator
Mujat, Claudia, Dogariu, Aristide, University of Central Florida
Abstract / Description
Light scattering-based techniques are being developed for non-invasive diagnostics of inhomogeneous media in various fields, such as medicine, biology, and material characterization. However, as most media of interest are highly scattering and have a complex structure, it is difficult to obtain a full analytical solution of the scattering problem without introducing approximations and assumptions about the properties of the system under consideration. Moreover, most of the previous studies...
Show moreLight scattering-based techniques are being developed for non-invasive diagnostics of inhomogeneous media in various fields, such as medicine, biology, and material characterization. However, as most media of interest are highly scattering and have a complex structure, it is difficult to obtain a full analytical solution of the scattering problem without introducing approximations and assumptions about the properties of the system under consideration. Moreover, most of the previous studies deal with idealized scattering situations, rarely encountered in practice. This dissertation provides new analytical, numerical, and experimental solutions to describe subtle effects introduced by the properties of the light sources, and by the boundaries, absorption and morphology of the investigated media. A novel Monte Carlo simulation was developed to describe the statistics of partially coherent beams after propagation through inhomogeneous media. The Monte Carlo approach also enabled us to study the influence of the refractive index contrast on the diffusive processes, to discern between different effects of absorption in multiple scattering, and to support experimental results on inhomogeneous media with complex morphology. A detailed description of chromatic effects in scattering was used to develop new models that explain the spectral dependence of the detected signal in applications such as imaging and diffuse reflectance measurements. The quantitative and non-invasive characterization of inhomogeneous media with complex structures, such as porous membranes, diffusive coatings, and incipient lesions in natural teeth was then demonstrated.
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Date Issued
2004
Identifier
CFE0000048, ucf:46143
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000048
A Framework for Measuring Return on Investment for Healthcare Simulation-Based Training
Title
A Framework for Measuring Return on Investment for Healthcare Simulation-Based Training.
Creator
Bukhari, Hatim, Rabelo, Luis, Elshennawy, Ahmad, Goldiez, Brian, Andreatta, Pamela, University of Central Florida
Abstract / Description
In the healthcare sector, providing high-quality service in a safe environment for both patient and staff is an obvious and ultimate major objective. Training is an essential component for achieving this important objective. Most organizations acknowledge that employee simulation-based training programs are an important part of the human capital strategy, yet few have effectively succeeded in quantifying the real and precise ROI of this type of investment. Therefore, if the training is...
Show moreIn the healthcare sector, providing high-quality service in a safe environment for both patient and staff is an obvious and ultimate major objective. Training is an essential component for achieving this important objective. Most organizations acknowledge that employee simulation-based training programs are an important part of the human capital strategy, yet few have effectively succeeded in quantifying the real and precise ROI of this type of investment. Therefore, if the training is perceived as a waste of resources and its ROI is not clearly recognized, it will be the first option to cut when the budget cut is needed.The various intangible benefits of healthcare simulation-based training are very difficult to quantify. In addition, there was not a unified way to count for the different cost and benefits to provide a justifiable ROI. Quantifying the qualitative and intangible benefits of medical training simulator needed a framework that helps to identify and convert qualitative and intangible benefits into monetary value so it can be considered in the ROI evaluation.This research is a response to the highlighted importance of developing a comprehensive framework that has the capability to take into consideration the wide range of benefits that simulation-based training can bring to the healthcare system taking into consideration the characteristics of this specific field of investment. The major characteristics of investment in this field include the uncertainty, the qualitative nature of the major benefits, and the diversity and the wide range of applications.This comprehensive framework is an integration of several methodologies and tools. It consists of three parts. The first part of the framework is the benefits and cost structure, which pays special attention to the qualitative and intangible benefits by considering the Value Measurement methodology (VMM) and other previously existing models. The second part of the framework is important to deal with the uncertainty associated with this type of investment. Monte Carlo simulation is a tool that considered multiple scenarios of input sets instead of a single set of inputs. The third part of the framework considers an advanced value analysis of the investment. It goes beyond the discounted cash flow (DCF) methodologies like net present value (NPV) that consider a single scenario for the cash flow to Real Options Analysis that consider the flexibility over the lifetime of the investment when evaluating the value of the investment. This framework has been validated through case studies.
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Date Issued
2017
Identifier
CFE0006859, ucf:51750
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006859
MONTE CARLO SIMULATION OF HOLE TRANSPORT AND TERAHERTZ AMPLIFICATION IN MULTILAYER DELTA DOPED SEMICONDUCTOR STRUCTURES
Title
MONTE CARLO SIMULATION OF HOLE TRANSPORT AND TERAHERTZ AMPLIFICATION IN MULTILAYER DELTA DOPED SEMICONDUCTOR STRUCTURES.
Creator
Dolguikh, Maxim, Peale, Robert, University of Central Florida
Abstract / Description
Monte Carlo method for the simulation of hole dynamics in degenerate valence subbands of cubic semiconductors is developed. All possible intra- and inter-subband scattering rates are theoretically calculated for Ge, Si, and GaAs. A far-infrared laser concept based on intersubband transitions of holes in p-type periodically delta-doped semiconductor films is studied using numerical Monte-Carlo simulation of hot hole dynamics. The considered device consists of monocrystalline pure Ge layers...
Show moreMonte Carlo method for the simulation of hole dynamics in degenerate valence subbands of cubic semiconductors is developed. All possible intra- and inter-subband scattering rates are theoretically calculated for Ge, Si, and GaAs. A far-infrared laser concept based on intersubband transitions of holes in p-type periodically delta-doped semiconductor films is studied using numerical Monte-Carlo simulation of hot hole dynamics. The considered device consists of monocrystalline pure Ge layers periodically interleaved with delta-doped layers and operates with vertical or in-plane hole transport in the presence of a perpendicular in-plane magnetic field. Inversion population on intersubband transitions arises due to light hole accumulation in E B fields, as in the bulk p-Ge laser. However, the considered structure achieves spatial separation of hole accumulation regions from the doped layers, which reduces ionized-impurity and carrier-carrier scattering for the majority of light holes. This allows remarkable increase of the gain in comparison with bulk p-Ge lasers. Population inversion and gain sufficient for laser operation are expected up to 77 K. Test structures grown by chemical vapor deposition demonstrate feasibility of producing the device with sufficient active thickness to allow quasioptical electrodynamic cavity solutions. The same device structure is considered in GaAs. The case of Si is much more complicated due to strong anisotropy of the valence band. The primary new result for Si is the first consideration of the anisotropy of optical phonon scattering for hot holes.
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Date Issued
2005
Identifier
CFE0000863, ucf:46672
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000863
Predictive Modeling of Functional Materials for Catalytic and Sensor Applications
Title
Predictive Modeling of Functional Materials for Catalytic and Sensor Applications.
Creator
Rawal, Takat, Rahman, Talat, Chang, Zenghu, Leuenberger, Michael, Zou, Shengli, University of Central Florida
Abstract / Description
The research conducted in my dissertation focuses on theoretical and computational studies of the electronic and geometrical structures, and the catalytic and optical properties of functional materials in the form of nano-structures, extended surfaces, two-dimensional systems and hybrid structures. The fundamental aspect of my research is to predict nanomaterial properties through ab-initio calculations using methods such as quantum mechanical density functional theory (DFT) and kinetic Monte...
Show moreThe research conducted in my dissertation focuses on theoretical and computational studies of the electronic and geometrical structures, and the catalytic and optical properties of functional materials in the form of nano-structures, extended surfaces, two-dimensional systems and hybrid structures. The fundamental aspect of my research is to predict nanomaterial properties through ab-initio calculations using methods such as quantum mechanical density functional theory (DFT) and kinetic Monte Carlo simulation, which help rationalize experimental observations, and ultimately lead to the rational design of materials for the electronic and energy-related applications. Focusing on the popular single-layer MoS2, I first show how its hybrid structure with 29-atom transition metal nanoparticles (M29 where M=Cu, Ag, and Au) can lead to composite catalysts suitable for oxidation reactions. Interestingly, the effect is found to be most pronounced for Au29 when MoS2 is defect-laden (S vacancy row). Second, I show that defect-laden MoS2 can be functionalized either by deposited Au nanoparticles or when supported on Cu(111) to serve as a cost-effective catalyst for methanol synthesis via CO hydrogenation reactions. The charge transfer and electronic structural changes in these sub systems lead to the presence of 'frontier' states near the Fermi level, making the systems catalytically active. Next, in the emerging area of single metal atom catalysis, I provide rationale for the viability of single Pd sites stabilized on ZnO(101 ?0) as the active sites for methanol partial oxidation, an important reaction for the production of H2. We trace its excellent activity to the modified electronic structure of the single Pd site as well as neighboring Zn cationic sites. With the DFT-calculated activation energy barriers for a large set of reactions, we perform ab-initio kMC simulations to determine the selectivity of the products (CO2 and H2). These findings offer an opportunity for maximizing the efficiency of precious metal atoms, and optimizing their activity and selectivity (for desired products). In related work on extended surfaces while trying to explain the Scanning Tunneling Microscopy images observed by our experimental collaborators, I discovered a new mechanism involved in the process of Ag vacancy formation on Ag(110), in the presence of O atoms which leads to the reconstruction and eventually oxidation of the Ag surface. In a similar vein, I was able to propose a mechanism for the orange photoluminescence (PL), observed by our experimental collaborators, of a coupled system of benzylpiperazine (BZP) molecule and iodine on a copper surface. Our results show that the adsorbed BZP and iodine play complimentary roles in producing the PL in the visible range. Upon photo-excitation of the BZP-I/CuI(111) system, excited electrons are transferred into the conduction band (CB) of CuI, and holes are trapped by the adatoms. The relaxation of holes into BZP HOMO is facilitated by its realignment. Relaxed holes subsequently recombine with excited electrons in the CB of the CuI film, thus producing a luminescence peak at ~2.1 eV. These results can be useful for forensic applications in detecting illicit substances.
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Date Issued
2017
Identifier
CFE0006783, ucf:51813
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006783
Modeling social norms in real-world agent-based simulations
Title
Modeling social norms in real-world agent-based simulations.
Creator
Beheshti, Rahmatollah, Sukthankar, Gita, Boloni, Ladislau, Wu, Annie, Swarup, Samarth, University of Central Florida
Abstract / Description
Studying and simulating social systems including human groups and societies can be a complex problem. In order to build a model that simulates humans' actions, it is necessary to consider the major factors that affect human behavior. Norms are one of these factors: social norms are the customary rules that govern behavior in groups and societies. Norms are everywhere around us, from the way people handshake or bow to the clothes they wear. They play a large role in determining our behaviors....
Show moreStudying and simulating social systems including human groups and societies can be a complex problem. In order to build a model that simulates humans' actions, it is necessary to consider the major factors that affect human behavior. Norms are one of these factors: social norms are the customary rules that govern behavior in groups and societies. Norms are everywhere around us, from the way people handshake or bow to the clothes they wear. They play a large role in determining our behaviors. Studies on norms are much older than the age of computer science, since normative studies have been a classic topic in sociology, psychology, philosophy and law. Various theories have been put forth about the functioning of social norms. Although an extensive amount of research on norms has been performed during the recent years, there remains a significant gap between current models and models that can explain real-world normative behaviors. Most of the existing work on norms focuses on abstract applications, and very few realistic normative simulations of human societies can be found. The contributions of this dissertation include the following: 1) a new hybrid technique based on agent-based modeling and Markov Chain Monte Carlo is introduced. This method is used to prepare a smoking case study for applying normative models. 2) This hybrid technique is described using category theory, which is a mathematical theory focusing on relations rather than objects. 3) The relationship between norm emergence in social networks and the theory of tipping points is studied. 4) A new lightweight normative architecture for studying smoking cessation trends is introduced. This architecture is then extended to a more general normative framework that can be used to model real-world normative behaviors. The final normative architecture considers cognitive and social aspects of norm formation in human societies. Normative architectures based on only one of these two aspects exist in the literature, but a normative architecture that effectively includes both of these two is missing.
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Date Issued
2015
Identifier
CFE0005577, ucf:50244
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005577
CMOS RF CITUITS VARIABILITY AND RELIABILITY RESILIENT DESIGN, MODELING, AND SIMULATION
Title
CMOS RF CITUITS VARIABILITY AND RELIABILITY RESILIENT DESIGN, MODELING, AND SIMULATION.
Creator
Liu, Yidong, Yuan, Jiann-Shiun, University of Central Florida
Abstract / Description
The work presents a novel voltage biasing design that helps the CMOS RF circuits resilient to variability and reliability. The biasing scheme provides resilience through the threshold voltage (VT) adjustment, and at the mean time it does not degrade the PA performance. Analytical equations are established for sensitivity of the resilient biasing under various scenarios. Power Amplifier (PA) and Low Noise Amplifier (LNA) are investigated case by case through modeling and experiment. PTM 65nm...
Show moreThe work presents a novel voltage biasing design that helps the CMOS RF circuits resilient to variability and reliability. The biasing scheme provides resilience through the threshold voltage (VT) adjustment, and at the mean time it does not degrade the PA performance. Analytical equations are established for sensitivity of the resilient biasing under various scenarios. Power Amplifier (PA) and Low Noise Amplifier (LNA) are investigated case by case through modeling and experiment. PTM 65nm technology is adopted in modeling the transistors within these RF blocks. A traditional class-AB PA with resilient design is compared the same PA without such design in PTM 65nm technology. Analytical equations are established for sensitivity of the resilient biasing under various scenarios. A traditional class-AB PA with resilient design is compared the same PA without such design in PTM 65nm technology. The results show that the biasing design helps improve the robustness of the PA in terms of linear gain, P1dB, Psat, and power added efficiency (PAE). Except for post-fabrication calibration capability, the design reduces the majority performance sensitivity of PA by 50% when subjected to threshold voltage (VT) shift and 25% to electron mobility (¼n) degradation. The impact of degradation mismatches is also investigated. It is observed that the accelerated aging of MOS transistor in the biasing circuit will further reduce the sensitivity of PA. In the study of LNA, a 24 GHz narrow band cascade LNA with adaptive biasing scheme under various aging rate is compared to LNA without such biasing scheme. The modeling and simulation results show that the adaptive substrate biasing reduces the sensitivity of noise figure and minimum noise figure subject to process variation and device aging such as threshold voltage shift and electron mobility degradation. Simulation of different aging rate also shows that the sensitivity of LNA is further reduced with the accelerated aging of the biasing circuit. Thus, for majority RF transceiver circuits, the adaptive body biasing scheme provides overall performance resilience to the device reliability induced degradation. Also the tuning ability designed in RF PA and LNA provides the circuit post-process calibration capability.
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Date Issued
2011
Identifier
CFE0003595, ucf:48861
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0003595
On Distributed Estimation for Resource Constrained Wireless Sensor Networks
Title
On Distributed Estimation for Resource Constrained Wireless Sensor Networks.
Creator
Sani, Alireza, Vosoughi, Azadeh, Rahnavard, Nazanin, Wei, Lei, Atia, George, Chatterjee, Mainak, University of Central Florida
Abstract / Description
We study Distributed Estimation (DES) problem, where several agents observe a noisy version of an underlying unknown physical phenomena (which is not directly observable), and transmit a compressed version of their observations to a Fusion Center (FC), where collective data is fused to reconstruct the unknown. One of the most important applications of Wireless Sensor Networks (WSNs) is performing DES in a field to estimate an unknown signal source. In a WSN battery powered geographically...
Show moreWe study Distributed Estimation (DES) problem, where several agents observe a noisy version of an underlying unknown physical phenomena (which is not directly observable), and transmit a compressed version of their observations to a Fusion Center (FC), where collective data is fused to reconstruct the unknown. One of the most important applications of Wireless Sensor Networks (WSNs) is performing DES in a field to estimate an unknown signal source. In a WSN battery powered geographically distributed tiny sensors are tasked with collecting data from the field. Each sensor locally processes its noisy observation (local processing can include compression,dimension reduction, quantization, etc) and transmits the processed observation over communication channels to the FC, where the received data is used to form a global estimate of the unknown source such that the Mean Square Error (MSE) of the DES is minimized. The accuracy of DES depends on many factors such as intensity of observation noises in sensors, quantization errors in sensors, available power and bandwidth of the network, quality of communication channels between sensors and the FC, and the choice of fusion rule in the FC. Taking into account all of these contributing factors and implementing a DES system which minimizes the MSE and satisfies all constraints is a challenging task. In order to probe into different aspects of this challenging task we identify and formulate the following three problems and address them accordingly:1- Consider an inhomogeneous WSN where the sensors' observations is modeled linear with additive Gaussian noise. The communication channels between sensors and FC are orthogonal power and bandwidth-constrained erroneous wireless fading channels. The unknown to be estimated is a Gaussian vector. Sensors employ uniform multi-bit quantizers and BPSK modulation. Given this setup, we ask: what is the best fusion rule in the FC? what is the best transmit power and quantization rate (measured in bits per sensor) allocation schemes that minimize the MSE? In order to answer these questions, we derive some upper bounds on global MSE and through minimizing those bounds, we propose various resource allocation schemes for the problem, through which we investigate the effect of contributing factors on the MSE.2- Consider an inhomogeneous WSN with an FC which is tasked with estimating a scalar Gaussian unknown. The sensors are equipped with uniform multi-bit quantizers and the communication channels are modeled as Binary Symmetric Channels (BSC). In contrast to former problem the sensors experience independent multiplicative noises (in addition to additive noise). The natural question in this scenario is: how does multiplicative noise affect the DES system performance? how does it affect the resource allocation for sensors, with respect to the case where there is no multiplicative noise? We propose a linear fusion rule in the FC and derive the associated MSE in closed-form. We propose several rate allocation schemes with different levels of complexity which minimize the MSE. Implementing the proposed schemes lets us study the effect of multiplicative noise on DES system performance and its dynamics. We also derive Bayesian Cramer-Rao Lower Bound (BCRLB) and compare the MSE performance of our porposed methods against the bound.As a dual problem we also answer the question: what is the minimum required bandwidth of thenetwork to satisfy a predetermined target MSE?3- Assuming the framework of Bayesian DES of a Gaussian unknown with additive and multiplicative Gaussian noises involved, we answer the following question: Can multiplicative noise improve the DES performance in any case/scenario? the answer is yes, and we call the phenomena as 'enhancement mode' of multiplicative noise. Through deriving different lower bounds, such as BCRLB,Weiss-Weinstein Bound (WWB), Hybrid CRLB (HCRLB), Nayak Bound (NB), Yatarcos Bound (YB) on MSE, we identify and characterize the scenarios that the enhancement happens. We investigate two situations where variance of multiplicative noise is known and unknown. Wealso compare the performance of well-known estimators with the derived bounds, to ensure practicability of the mentioned enhancement modes.
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Date Issued
2017
Identifier
CFE0006913, ucf:51698
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006913