2,461 research outputs found
Accurate estimating simultaneous switching noises by using application specific device modeling
Abstract In this paper, we study the simultaneous switching noise problem by using an application-specific modeling method.
A hybrid EKF and switching PSO algorithm for joint state and parameter estimation of lateral flow immunoassay models
This is the post-print version of the Article. The official published can be accessed from the link below - Copyright @ 2012 IEEEIn this paper, a hybrid extended Kalman filter (EKF) and switching particle swarm optimization (SPSO) algorithm is proposed for jointly estimating both the parameters and states of the lateral flow immunoassay model through available short time-series measurement. Our proposed method generalizes the well-known EKF algorithm by imposing physical constraints on the system states. Note that the state constraints are encountered very often in practice that give rise to considerable difficulties in system analysis and design. The main purpose of this paper is to handle the dynamic modeling problem with state constraints by combining the extended Kalman filtering and constrained optimization algorithms via the maximization probability method. More specifically, a recently developed SPSO algorithm is used to cope with the constrained optimization problem by converting it into an unconstrained optimization one through adding a penalty term to the objective function. The proposed algorithm is then employed to simultaneously identify the parameters and states of a lateral flow immunoassay model. It is shown that the proposed algorithm gives much improved performance over the traditional EKF method.This work was supported in part by the International Science and Technology Cooperation Project of China under Grant
2009DFA32050, Natural Science Foundation of China under Grants 61104041, International Science and Technology Cooperation Project of Fujian Province of China under Grant
2009I0016
Empirical timing analysis of CPUs and delay fault tolerant design using partial redundancy
The operating clock frequency is determined by the longest signal propagation
delay, setup/hold time, and timing margin. These are becoming less predictable with
the increasing design complexity and process miniaturization. The difficult challenge
is then to ensure that a device operating at its clock frequency is error-free with
quantifiable assurance. Effort at device-level engineering will not suffice for these
circuits exhibiting wide process variation and heightened sensitivities to operating
condition stress. Logic-level redress of this issue is a necessity and we propose a
design-level remedy for this timing-uncertainty problem.
The aim of the design and analysis approaches presented in this dissertation is to
provide framework, SABRE, wherein an increased operating clock frequency can be
achieved. The approach is a combination of analytical modeling, experimental analy-
sis, hardware /time-redundancy design, exception handling and recovery techniques.
Our proposed design replicates only a necessary part of the original circuit to avoid
high hardware overhead as in triple-modular-redundancy (TMR). The timing-critical
combinational circuit is path-wise partitioned into two sections. The combinational
circuits associated with long paths are laid out without any intrusion except for the
fan-out connections from the first section of the circuit to a replicated second section
of the combinational circuit. Thus only the second section of the circuit is replicated.
The signals fanning out from the first section are latches, and thus are far shorter than the paths spanning the entire combinational circuit. The replicated circuit is timed
at a subsequent clock cycle to ascertain relaxed timing paths. This insures that the
likelihood of mistiming due to stress or process variation is eliminated. During the
subsequent clock cycle, the outcome of the two logically identical, yet time-interleaved,
circuit outputs are compared to detect faults. When a fault is detected, the retry sig-
nal is triggered and the dynamic frequency-step-down takes place before a pipe flush,
and retry is issued. The significant timing overhead associated with the retry is offset
by the rarity of the timing violation events. Simulation results on ISCAS Benchmark
circuits show that 10% of clock frequency gain is possible with 10 to 20 % of hardware
overhead of replicated timing-critical circuit
Modeling and Estimation for Maneuvering Target Tracking with Inertial Systems using Interacting Multiple Models
Projecte final de carrea realitzat en col.laboracio amb Centre Tecnològic de
Telecomunicacions de CatalunyaThe aim of this Thesis is to study and develop Estimation Technique that enhances the
Dynamic Tracking capability of Maneuvering Targets based using Inertial Systems.
Inertial Measurement Systems have measurement biases and drifts and properly
estimating their errors is a real time problem. Moreover, different targets perform
different types of maneuvers during different stages of their trajectory and as such it is
not possible to obtain accurate tracking of target maneuvers using a filters based on
conventional single model approach. As such, a technique is required which is dynamic
in both estimating and filtering the errors in inertial measurements and in switching to
appropriate motion models according to the current maneuver of the vehicle. This
thesis suggests and evaluates ‘Interacting Multiple Models (IMM)’ scheme for the
solution to the above problem. Performance of the IMM scheme is proven over
conventional single model based filters like Kalman Filter through both simulations and
real target tracking
Nonlinear bilateral teleoperation using extended active observer for force estimation and disturbance suppression
A novel nonlinear teleoperation algorithm for simultaneous inertial parameters and force estimation at the master and slave sides of the teleoperation system is proposed. The scheme, called Extended Active Observer (EAOB), is an extension of the existing active observer. It provides effective force tracking at the master side with accurate position tracking at the slave side in the presence of inertial parameter variation and measurement noise. The proposed method only requires the measurement of robot position, and as a result significantly reduces the difficulty and cost of implementing bilateral teleoperation systems. The approach is described and its stability is analytically verified. The performance of the method is validated through computer simulation and compared with the Nicosia observer-based controller. According to the results, EAOB outperforms the Nicosia observer method and effectively rejects noise
Quantifiable Assurance: From IPs to Platforms
Hardware vulnerabilities are generally considered more difficult to fix than
software ones because they are persistent after fabrication. Thus, it is
crucial to assess the security and fix the vulnerabilities at earlier design
phases, such as Register Transfer Level (RTL) and gate level. The focus of the
existing security assessment techniques is mainly twofold. First, they check
the security of Intellectual Property (IP) blocks separately. Second, they aim
to assess the security against individual threats considering the threats are
orthogonal. We argue that IP-level security assessment is not sufficient.
Eventually, the IPs are placed in a platform, such as a system-on-chip (SoC),
where each IP is surrounded by other IPs connected through glue logic and
shared/private buses. Hence, we must develop a methodology to assess the
platform-level security by considering both the IP-level security and the
impact of the additional parameters introduced during platform integration.
Another important factor to consider is that the threats are not always
orthogonal. Improving security against one threat may affect the security
against other threats. Hence, to build a secure platform, we must first answer
the following questions: What additional parameters are introduced during the
platform integration? How do we define and characterize the impact of these
parameters on security? How do the mitigation techniques of one threat impact
others? This paper aims to answer these important questions and proposes
techniques for quantifiable assurance by quantitatively estimating and
measuring the security of a platform at the pre-silicon stages. We also touch
upon the term security optimization and present the challenges for future
research directions
A Survey of Positioning Systems Using Visible LED Lights
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.Peer reviewe
Composite Disturbance Filtering: A Novel State Estimation Scheme for Systems With Multi-Source, Heterogeneous, and Isomeric Disturbances
State estimation has long been a fundamental problem in signal processing and
control areas. The main challenge is to design filters with ability to reject
or attenuate various disturbances. With the arrival of big data era, the
disturbances of complicated systems are physically multi-source, mathematically
heterogenous, affecting the system dynamics via isomeric (additive,
multiplicative and recessive) channels, and deeply coupled with each other. In
traditional filtering schemes, the multi-source heterogenous disturbances are
usually simplified as a lumped one so that the "single" disturbance can be
either rejected or attenuated. Since the pioneering work in 2012, a novel state
estimation methodology called {\it composite disturbance filtering} (CDF) has
been proposed, which deals with the multi-source, heterogenous, and isomeric
disturbances based on their specific characteristics. With the CDF, enhanced
anti-disturbance capability can be achieved via refined quantification,
effective separation, and simultaneous rejection and attenuation of the
disturbances. In this paper, an overview of the CDF scheme is provided, which
includes the basic principle, general design procedure, application scenarios
(e.g. alignment, localization and navigation), and future research directions.
In summary, it is expected that the CDF offers an effective tool for state
estimation, especially in the presence of multi-source heterogeneous
disturbances
Research on performance enhancement for electromagnetic analysis and power analysis in cryptographic LSI
制度:新 ; 報告番号:甲3785号 ; 学位の種類:博士(工学) ; 授与年月日:2012/11/19 ; 早大学位記番号:新6161Waseda Universit
Characterization, Classification, and Genesis of Seismocardiographic Signals
Seismocardiographic (SCG) signals are the acoustic and vibration induced by cardiac activity measured non-invasively at the chest surface. These signals may offer a method for diagnosing and monitoring heart function. Successful classification of SCG signals in health and disease depends on accurate signal characterization and feature extraction. In this study, SCG signal features were extracted in the time, frequency, and time-frequency domains. Different methods for estimating time-frequency features of SCG were investigated. Results suggested that the polynomial chirplet transform outperformed wavelet and short time Fourier transforms. Many factors may contribute to increasing intrasubject SCG variability including subject posture and respiratory phase. In this study, the effect of respiration on SCG signal variability was investigated. Results suggested that SCG waveforms can vary with lung volume, respiratory flow direction, or a combination of these criteria. SCG events were classified into groups belonging to these different respiration phases using classifiers, including artificial neural networks, support vector machines, and random forest. Categorizing SCG events into different groups containing similar events allows more accurate estimation of SCG features. SCG feature points were also identified from simultaneous measurements of SCG and other well-known physiologic signals including electrocardiography, phonocardiography, and echocardiography. Future work may use this information to get more insights into the genesis of SCG
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