A review of compact modeling for phase change memory

Phase change memory(PCM)attracts wide attention for the memory-centric computing and neuromorphic comput-ing.For circuit and system designs,PCM compact models are mandatory and their status are reviewed in this work.Macro mod-els and physics-based models have been proposed in different stages of the PCM technology developments.Compact model-ing of PCM is indeed more complex than the transistor modeling due to their multi-physics nature including electrical,thermal and phase transition dynamics as well as their interactions.Realizations of the PCM operations including threshold switching,set and reset programming in these models are diverse,which also differs from the perspective of circuit simulations.For the purpose of efficient and reliable designs of the PCM technology,open issues and challenges of the compact modeling are also discussed.     

Scalable perceptual audio representation with an adaptive three time-scale sinusoidal signal model

This work is concerned with the development and optimization of a signal model for scalable perceptual audio coding at low bit rates. A complementary two-part signal model consisting of Sines plus Noise (SN) is described. The paper presents essentially a fundamental enhancement to the sinusoidal modeling component. The enhancement involves an audio signal scheme based on carrying out overlap-add sinusoidal modeling at three successive time scales, large, medium, and small. The sinusoidal modeling is done in an analysis-by-synthesis overlapadd manner across the three scales by using a psychoacoustically weighted matching pursuits. The sinusoidal modeling residual at the first scale is passed to the smaller scales to allow for the modeling of various signal features at appropriate resolutions. This approach greatly helps to correct the pre-echo inherent in the sinusoidal model. This improves the perceptual audio quality upon our previous work of sinusoidal modeling while using the same number of sinusoids. The most obvious application for the SN model is in scalable, high fidelity audio coding and signal modification.     

Double-πfully scalable model for on-chip spiral inductors

A novel double-πequivalent circuit model for on-chip spiral inductors is presented.A hierarchical structure, similar to that of MOS models is introduced.This enables a strict partition of the geometry scaling in the global model and the model equations in the local model.The major parasitic effects,including the skin effect,the proximity effect,the inductive and capacitive loss in the substrate,and the distributed effect,are analytically calculated with geometric and process parameters in the local-level.As accurate values of the layout and process parameters are difficult to obtain,a set of model parameters is introduced to correct the errors caused by using these given inaccurate layout and process parameters at the local level.Scaling rules are defined to enable the formation of models that describe the behavior of the inductors of a variety of geometric dimensions.A series of asymmetric inductors with different geometries are fabricated on a standard 0.18-μm SiGe BiCMOS process with 100Ω/cm substrate resistivity to verify the proposed model.Excellent agreement has been obtained between the measured results and the proposed model over a wide frequency range.     

Building Modeling Tools Based on Metamodeling and Product Line Technologies

With the evolution of existing modeling languages and the emergence of more and more new modeling languages, it is necessary to rapidly build the corre-sponding software modeling tools with good quality. However, modeling tools for larger modeling languages are usu-ally diversity in function and complexity in implementation technology. Taking building modeling tools as a domain, this paper presents an approach to building software mod- eling tools based on metamodeling and product line tech- nologies. The paper provides the concept system of the ap- proach and a feature model from diverse functions of mod- eling tools in order to specify the commonality and vari- ability of the tools by deeply making the domain analysis, discusses the design and implementation of a general tool framework that provides the conveniences for reusing com- ponents and generating code for components, and specifies the mapping between the feature model and the compo- nents for modeling tools.     

A Formal Approach for Obligation Analysis of E-Commerce

Existing methods for modeling Ecommerce systems （ECSs） focus mostly on either mathematically abstract verification or graphical modeling, and cannot explicitly describe and analyze the obligations of partners. This work presents a new class of Labeled Petri nets for the modeling and analysis of ECSs. And the life cycle of a case and the time/date of firing an action are considered. It can model graphically the dynamic behavior of the systems, and analyze elegantly the obligations. This approach is illustrated with a nontrivial example of the modeling and analysis of the trading process of the Purchase transaction in the Internet open trading protocol.     

Modeling and Analysis of Pulse Skip Modulation

The state space average model and the large signal models of Pulse Skip Modulation （PSM） mode are given in this paper. Farther more, based on these models and simulations of PSM converter circuits, the analysis of the characteristics of PSM converter is described in this paper, of which include efficiency, frequency spectrum analysis, output voltage ripple, response speed and interference rejection capability. Compared with PWM control mode, PSM converter has high efficiency, especially with fight loads, quick response, good interference rejection and good EMC characteristic. Improved PSM slightly, it could be a kind of good independent regulating mode during the whole operating process for a DC-DC converter. Finally, some experimental results are also presented in this paper.     

Double-π fully scalable model for on-chip spiral inductors

A novel double-π equivalent circuit model for on-chip spiral inductors is presented.A hierarchical structure,similar to that of MOS models is introduced.This enables a strict partition of the geometry ...     

Study and Design of Spiral Bent Waveguide Configuration

A new version of the scalar transverse electric（TE） wave equation in the bent waveguide is introduced. Then. TE polarized field in curved single-mode waveguides is analyzed by using the finite- difference beam propagation method（FD-BPM）. The bending loss in bent waveguides is gotten for the optical fields obtained from BPM and comparisons are made among losses of the waveguides with various curvature radiuses, refractive index differences and cross sections. Based on the results, the design of spiral bent waveguide configuration is proposed as follows： refractive index difference being of 0. 007, both width and thickness of waveguides being of 6 μm, the curvature radius in the spiral centre being of 4 mm, and the bending loss coefficient of the designed spiral bent waveguide being of 0. 302 3 dB/cm.     

Graph theory for FPGA minimum configurations

A traditional bottom-up modeling method for minimum configuration numbers is adopted for the study of FPGA minimum configurations.This method is limited if a large number of LUTs and multiplexers are presented. Since graph theory has been extensively applied to circuit analysis and test,this paper focuses on the modeling FPGA configurations.In our study,an internal logic block and interconnections of an FPGA are considered as a vertex and an edge connecting two vertices in the graph,respectively.A top-down modeling method is proposed in the paper to achieve minimum configuration numbers for CLB and IOB.Based on the proposed modeling approach and exhaustive analysis,the minimum configuration numbers for CLB and IOB are five and three,respectively.     

Intelligent Cost Modeling Based on Soft Computing for Avionics Systems

In parametric cost estimating, objections to using statistical Cost Estimating Relationships （CERs） and parametric models include problems of low statistical significance due to limited data points, biases in the underlying data, and lack of robustness. Soft Computing （SC） technologies are used for building intelligent cost models. The SC models are systemically evaluated based on their training and prediction of the historical cost data of airborne avionics systems. Results indicating the strengths and weakness of each model are presented. In general, the intelligent cost models have higher prediction precision, better data adaptability, and stronger self-learning capability than the regression CERs.     

Graph coloring based channel assignment framework for rural wireless mesh networks

IEEE 802.11 based wireless mesh networks with directional antennas are expected to be a new promising technology and an economic approach for providing wireless broadband services in rural areas. In this paper, we discuss interference models and address how they can affect the design of channel assignment in rural mesh networks. We present a new channel assignment framework based on graph coloring for rural wireless mesh networks. The goal of the framework is to allow synchronously transmitting or receiving data from multiple neighbor links at the same time, and continuously doing full-duplex data transfer on every link, creating an efficient rural mesh network without interference. Channel assignment is shown to be NP-hard. We frame this channel allocation problem in terms of Adjacent Vertex Distinguishing Edge Coloring （AVDEC）. Detailed assignment results on grid topology are presented and discussed. Furthermore, we design an algorithm. Finally, we evaluate the perform- ance of the proposed algorithm through extensive simulations and show the algorithm is effective to the regular grid topologies, and the number of colors used by the algorithm is upper bounded by A ~ 1. Hence the algorithm guarantees that the number of channels available in standards such as IEEE 802.11a is sufficient to have a valid AVDEC for many grid topologies. We also evaluate the proposed algorithm for arbitrary graphs. The algorithm provides a lower upper bound on the minimum number of channels to the AVDEC index channel assignment problem.     

Computer Modeling and Simulation Evaluation of High Power LED Sources for Secondary Optical Design

Proposed and demonstrated is a novel computer modeling method for high power light emitting diodes（LEDs）. It contains geometrical structure and optical property of high power LED as well as LED dies definition with its spatial and angular distribution. Merits and non-merits of traditional modeling methods when applied to high power LEDs based on secondary optical design are discussed. Two commercial high power LEDs are simulated using the proposed computer modeling method. Correlation coefficient is proposed to compare and analyze the simulation results and manufacturing specifications. The source model is precisely demonstrated by obtaining above 99% in correlation coefficient with different surface incident angle intervals.     

Model and Simulation of Multipath Error in DLL for GPS Receiver

Although different multipath error models of Delay lock loop （DLL） used in GPS receiver are established, they have never been put together for comparison. Furthermore, no universal simulation method is developed to get a fair comparison among these models. A new model with implicate expression is hence proposed for the coherent DLL and the noncoherent Dot-product （DOT） power mode DLL. Meanwhile, a new simulation method based on the anonymous function in Matlab, which is especially suitable for models with implicit expressions is also proposed to compare the new model with the existing ones. The theoretical analysis and simulation results show that the existing models are the special case of the proposed one. The new simulation method can be used for the comparison of different multipath error models and the multipath error analysis of other DLLs for which only the implicit model is available.     

Machine-Learning-Assisted Optimization and Its Application to Antenna Designs: Opportunities and Challenges

With the rapid development of modern wireless communications and radar, antennas and arrays are becoming more complex, therein having, e.g., more degrees of design freedom, integration and fabrication constraints and design objectives. While fullwave electromagnetic simulation can be very accurate and therefore essential to the design process, it is also very time consuming, which leads to many challenges for antenna design, optimization and sensitivity analysis(SA). Recently, machine-learning-assisted optimization(MLAO) has been widely introduced to accelerate the design process of antennas and arrays. Machine learning(ML) methods, including Gaussian process regression, support vector machine(SVM) and artificial neural networks(ANNs), have been applied to build surrogate models of antennas to achieve fast response prediction. With the help of these ML methods, various MLAO algorithms have been proposed for different applications. A comprehensive survey of recent advances in ML methods for antenna modeling is first presented. Then, algorithms for ML-assisted antenna design, including optimization and SA, are reviewed. Finally, some challenges facing future MLAO for antenna design are discussed.     

An Efficient Approach to Odometric Non-systematic Error Modeling for Mobile Robots

Odometric non-systematic error modeling for mobile robot is the basis of localization. Most of the approaches to odometric non-systematic error modeling are designed for some special driving-type robots nowadays. And the long-term odometric errors without bound, which degrade the localization precision after long-distance movement, are not often capable of being compensated in real-time. Therefore, a general approach to odometric nonsystematic error modeling for mobile robot is proposed in regard to both synchronous drive roller robots and diiTerential drive roller robots. The approach assumes that the robot path is approximated to circular arcs. The function relationships, between the odometric process input and non-systematic errors, are derived on the basis of the odometric error transformation rules, further the accumulative errors of odometry in the localization process are compensated in real-time. The experiments show that the compensation of non-systematic error can reduce the odo- metric long-term errors efficiently, and improve the localization precision remarkably.     

Maneuvering Multi-target Tracking Using the Multi-model Cardinalized Probability Hypothesis Density Filter

Tracking an unknown and time-varying number of maneuvering targets is a challenging problem in the presence of noise, clutter uncertainties in target maneuvers, data association, and detection. To account for this problem, a multi-model extension of the Cardinalized probability hypothesis density （CPHD） filter is proposed in this paper. Additionally, a particle implementation and a Gaussian mixture implementation of the proposed extension are given for generic models and linear Gaussian models, respectively. The effectiveness of the extension is illustrated through Monte Carlo simulation.     

基于预建模单元的宽带毫米波CMOS晶体管可变栅宽高效建模

Thisworkpresentsahighlyefficientapproachforbroadbandmodelingofmillimeter-waveCMOSFETs with gate width scalability by using pre-modeled cells. Only a few devices with varied gate width are required to be measured and modeled with fixed models, and later used as pre-modeled cells. Then a target device with the desired gate width is constructed by choosing appropriate cells and connecting them with a wiring network. The corresponding scalable model is constructed by incorporating the fixed models of the cells used in the target device and the scalable model of the connection wires. The proposed approach is validated by experiments on 65-nm CMOS process up to 40 GHz and across a wide range of gate widths.     

应用于65nm CMOS技术节点漏电流分析的精确快速的查表模型

Novel physical models for leakage current analysis in 65 nm technology are proposed. Taking into consideration the process variations and emerging effects in nano-scaled technology, the presented models are capable of accurately estimating the subthreshold leakage current and junction tunneling leakage current in 65 nm technology. Based on the physical models, new table look-up models are developed and first applied to leakage current analysis in pursuit of higher simulation speed. Simulation results show that the novel physical models are in excellent agreement with the data measured from the foundry in the 65 nm process, and the proposed table look-up models can provide great computational efficiency by using suitable interpolation techniques. Compared with the traditional physical-based models, the table look-up models can achieve 2.5X speedup on average on a variety of industry circuits.