nils-herrmann/clean_scirepeval huggingface dataset:
On the parameter estimation of the harmonic, evanescent and purely indeterministic components of homogeneous random fields

A maximum-likelihood (ML) estimation procedure for the parameters of homogeneous random fields is presented. On the basis of a 2D Wold-like decomposition, the random field is decomposed into a sum of mutually orthogonal components of three types: purely indeterministic, harmonic, and generalized evanescent. Because, in general, a homogeneous random field is characterized by a mixed spectral distribution, parameter estimation techniques which are solely based on spectral density estimators are not adequate. An algorithm which results in a complete parameter estimation for the purely indeterministic and harmonic components of the homogeneous random field and in estimates for the evanescent component frequencies is presented. The new ML method produces highly accurate estimates of these parameters.<<ETX>>
A Nonlinear Electro-Thermal Scalable Model for High-Power RF LDMOS Transistors

A new nonlinear charge-conservative scalable dynamic electro-thermal compact model for laterally defused MOS (LDMOS) RF power transistors is described in this paper. The transistor is characterized using pulsed I-V and S-parameter measurements, to ensure isothermal conditions. A new extrinsic network and extrinsic parameter-extraction methodology is developed for high-power RF LDMOS transistor modeling, using manifold deembedding by electromagnetic simulation, and optimization of the extrinsic network parameter values over a broad frequency range. The intrinsic model comprises controlled charge and current sources that have been implemented using artificial neural networks, designed to permit accurate extrapolation of the transistor's performance outside of the measured data domain. A thermal sub-circuit is coupled to the nonlinear model. Large-signal validation of this new model shows a very good agreement with measurements at 2.14 GHz.
Joint utilization of fixed and variable-length codes for improving synchronization immunity for image transmission

Robust transmission of images is achieved by using fixed and variable-length coding together without much loss in compression efficiency. The probability distribution function of a DCT coefficient can be divided into two regions using a threshold, so that one portion contains roughly equiprobable transform coefficients. While fixed-length coding, which is a powerful solution to the synchronization problem, is used in this inner equiprobable region without sacrificing compression, the outer (saturating) region is reserved for variable-length codes. The proposed image coder first encodes the bit allocated DCT coefficients using a fixed-rate quantizer bank, then the saturated values for these coefficients are encoded using an entropy constrained scalar quantizer, followed by an arithmetic encoder. Our simulations show that the proposed encoder is appropriate for applications in which an acceptable quality must always be maintained in any channel condition.
Prediction of perceptual quality for mobile video using fuzzy inference systems

Along with the rapid growth in consumer adoption of modern portable devices, video streaming is expected to dominate a large share of the global internet traffic in the near future. In the wireless communications domain, this trend creates considerable challenges to consumers' quality of experience (QoE). From a consumer-focused vision, predicting perceptual video quality is extremely important for QoE-based service provisioning. However, available QoE measurement techniques that adopt a full reference model are impractical in real-time transmission since they require the original video sequence to be available at the receiver's end. Therefore, the primary aim of this study is to present a cross-layer no-reference prediction model for the perceptual quality of 3D video in the wireless domain. The contributions of this study are twofold: first, the impact of selected quality of service (QoS) parameters from both encoding and network levels on QoE is investigated. Also, the obtained QoS/QoE correlation is backed by thorough statistical analysis. Second, a prediction model based on fuzzy logic inference systems (FIS) is developed by mapping chosen QoS parameters to the measured QoE. This model enables a non-intrusive prediction of 3D visual quality. Conclusive results show a significantly high correlation between the predicted video quality and the objectively measured mean opinion scores (MOS).  MOS is also validated through methodical subjective assessments. For consumer's QoE, this study advances the development of reference-free video quality prediction models and QoE control methods for 3D video streaming.
Statistical Neuro-Space Mapping Technique for Large-Signal Modeling of Nonlinear Devices

A new technique, called statistical neuro-space mapping, is proposed for large-signal statistical modeling of nonlinear microwave devices. The proposed technique is an advance over a recent linear statistical mapping technique. It uses nonlinear mapping to overcome the accuracy limitations of the linear mapping in modeling large statistical variations among different devices. For a given population of device samples, the nominal device model is determined from dc, small-, and large-signal data. The behavior of a random device in the population is obtained by a nonlinear mapping from that of the nominal device. The unknown mapping function is represented by neural networks trained using dc and small-signal data of various devices in the population. A novel statistical mapping is formulated by introducing a compact set of statistical variables to control the mapping to map from the nominal device toward different devices in the population. A new training method is proposed for simultaneous statistical parameter extraction and neural-network training. The proposed technique is confirmed by statistical modeling of microwave transistor examples, and use of the models in statistical analyses of a two-stage amplifier. It is demonstrated that, for small or large statistical variations, the proposed technique outperforms the existing methods, using a minimum amount of expensive large-signal data to provide the most accurate large-signal statistical model.
AMULET1: A Asynchronous ARM Microprocessor

An asynchronous implementation of the ARM microprocessor has been developed using an approach based on Sutherland's Micropipelines. The design allows considerable internal asynchronous concurrency. This paper presents the rationale for the work, the organization of the chip, and the characteristics of the prototype silicon. The design displays unusual properties such as nondeterministic (but bounded) prefetch depth beyond a branch instruction, a data dependent throughput, and employs a novel register locking mechanism. This work demonstrates the feasibility of building complex asynchronous systems and gives an indication of the costs and benefits of the Micropipeline approach.
Out-lier removal algorithm for model-based coded video

Model-based coding extracts texture from images of objects and projects them onto computer models of the same objects. Low bit rate transmission is achieved by approximating the shape and movement of the objects and relaying the parameters to the decoder. To estimate the motion of the models a number of features must be accurately tracked inter-frame. The proposed algorithm employs a large displacement vector set, and then proceeds to iteratively remove points exhibiting large disagreement between the 2D translational field and a projection of the estimated 3D rotation. Subjective improvement in motion estimation and better quantitative agreement between motion fields are reported.
Using an agent based platform to map quality of service to experience in conventional and active networks

A quality of experience (QoE) metric is defined as being the user's perception of the network's QoS parameters. The QoE defines a combination of user satisfaction, understanding and interest. Using agents, network QoS parameters are controlled in an attempt to match the user's perceived QoE. The QoS is managed through an arbitrator using (a) a series of rules and reference tables and (b) the end-user feedback. Within the framework presented the user can change the QoS requirements at any time. It is believed that by empowering the user to select the quality according to expectation, QoE can be improved relative to the individual. A mapping to the perceived QoE is derived from a group of objective and subjective weighting factors associated to the QoS performance parameters. The framework has been validated by building a prototype. A series of experiments was conducted in which both a conventional and an active QoS mechanism was employed by the arbitrator. The QoE mapping has proved useful for understanding the relation between objective and subjective metrics in the experiments. From these measurements the QoE requirements and a general outlook of the network and the conditions at the time of the transmission may be inferred.
Multiphysics Modeling of RF and Microwave High-Power Transistors

In this paper, we present a multiphysics approach for the simulation of high-power RF and microwave transistors, in which electromagnetic, thermal, and nonlinear transistor models are linked together within a harmonic-balance circuit simulator. This approach is used to analyze a laterally diffused metal-oxide-semiconductor (LDMOS) transistor that has a total gate width of 102 mm and operates at 2.14 GHz. The transistor die is placed in a metal-ceramic package, with bond-wire arrays connecting the die to the package leads. The effects of three different gate bond-pad layouts on the transistor efficiency are studied. Through plots of the spatial distributions of the drain efficiency and the time-domain currents and voltages across the die, we reveal for the first time unique interactions between the electromagnetic effects of the layout and the microwave behavior of the large-die LDMOS power field-effect transistor.
Evaluating ALOS-PALSAR for Ice Monitoring - What Can L-band do for the North American Ice Service?

The Canadian Ice Service (CIS), the U.S. National Ice Center (NIC), and the International Ice Patrol (IIP), partners in the North American Ice Service (NAIS), have individually and jointly used airborne and spaceborne synthetic aperture radar data extensively for almost three decades in their daily ice monitoring operations. SAR's unique ability to penetrate clouds and weather make these data invaluable to the NAIS' efficient environmental stewardship and safe operation in Canadian and U.S. waters. Since 1992, solely C-Band satellite radar has been in use as operational SAR missions such as ERS 1 & 2, RADARSAT-1, and Envisat ASAR have selected it as the band of choice. With the launch of RADARSAT-2 on December 2007 and approved plans for Sentinel-1, the NAIS intends to continue utilizing C-Band data in its daily operations. However, it is important to understand the unique and complementary capabilities of other SAR bands. The January 2006 launch of the JAXA ALOS satellite and present availability of L-band SAR data from its PALSAR instrument provides a unique opportunity to assess L-band data for application to ice monitoring. ALOS/PALSAR availability also provides the potential for examining the synergies between L-Band data and C-Band data available from the current and planned C-Band missions. The existing literature suggests that the use of different frequencies could be advantageous in certain ice conditions, which is of interest to the NAIS because of the vastness of the geographical area monitored annually and the associated variations in ice regimes and conditions. This paper summarizes the preliminary results of a NAIS evaluation of near-coincident C-Band (RADARSAT-1) and L-Band data sets collected in various ice regimes. Through both quantitative and qualitative analysis we attempt to identify the unique and complementary sea ice information PALSAR can provide. In doing so, we identify the role these data could play in the NAIS' operational programs, both in a complementary role to existing C-Band SARs and its potential as a contingency platform. This work will also help us better understand the potential for future possible multi-frequency SAR platforms.
Enhanced MC-EZBC Scalable Video Coder

In this paper, we provide some recent extension to the scalable subband/wavelet video coder MC-EZBC. The enhanced MC-EZBC employs an adaptive motion-compensated temporal filter (MCTF) framework. Directional I-BLOCKs and overlapped block motion compensation (OBMC) further improve MCTF efficiency. A scalable motion vector coder based on CABAC is shown to improve the overall performance at low bitrates/resolution. Frequency rolloff is incorporated to reduce spatial aliasing at low resolution without PSNR loss at full resolution. Experimental results show that the new features significantly improve the performance of MC-EZBC. We provide several comparisons to other recent coders.
Linear signal synthesis using the Radon-Wigner transform

Thresholding the Radon-Wigner transform (RWT) followed by filtered backprojection to the time-frequency plane reduces noise and cross-term power for multicomponent linear-FM signals. Although the RWT is bilinear, it may be calculated as the magnitude-squared of two linear functions. In this paper, we derive a linear synthesis algorithm from the RWT and demonstrate its efficacy.
Circuit design study for a GaAs operational transconductance amplifier

A GaAs Operational Transconductance Amplifier IC with a bandwidth of over 1 GHz has been designed and fabricated, for use in active OTA-C filter designs at radio frequencies. The design uses a Gilbert cell tunable transconductor and a new MESFET current mirror structure, and has been fabricated using a commercial 0.5 μm MMIC process. (6 pages)
Fine Grain Adaptive FEC (FGA-FEC) Over Wireless Networks

In this paper, we extend our proposed FGA-FEC coding scheme, a generalized MD-FEC method, to wireless networks. To protect the encoded scalable video bitstream over a lossy channel and facilitate content adaptation at intermediate nodes, we use product codes based on BCH/CRC codes as row codes and RS codes as column codes. We give a fast algorithm to optimize the product codes within several iterations from a near optimal point. Simulations show good performance in both content adaptation and protection.
Delay dependent stability limits in high performance real-time visual servoing systems

This paper addresses the long-standing problem that visual feedback delay can drive a high bandwidth visual servoing system unstable. While some architectures become unstable with increasing image processing delay, we propose a novel visual servo implementation whose stability is independent of delay time. Performance decreases as image processing delay increases, but the system always remains stable. We demonstrate our new approach experimentally on a camera-pointing device. For those visual servo implementations that will become unstable with increased time delay, we propose an analytical method to find the upper limit of acceptable delay, using equations derived from the Nyquist stability criterion. The approach described in this paper is not only a useful tool for design and implementation of stable visual servoing systems, but also has general application to other dynamic systems with delay elements.
Sharing inertia load between multiple robots with active compliant grippers using trajectory pre-shaping

In this paper we propose a cooperative motion scheme that is able to control the sharing of gravitational and inertia load (forces required for load acceleration/deceleration) among multiple position-controlled robots. We adopt a clamped-free configuration, where a leader robot grasps the load directly and a follower robot grasps the load through a spring mounted on its end effector. While the leader travels the designated trajectory, a delta trajectory is added to the follower that supplies its share of inertia force by stretching/compressing the spring. The trajectory of the follower is pre-shaped to cancel out vibrations, therefore reducing the impact force on the robot mechanism. The spring also provides compliance in non-force-controlled directions to reduce internal forces. We analyze the influence of temporal error on both load sharing and internal force and propose a synchronization method to reduce this error to less than 1 ms. Every aspect of our scheme can be implemented with commercial robots without any modification of controller parameters or knowledge of the manipulator dynamics. Being able to execute our cooperative motion at a speed of 0.5 m per sec, it is much faster than impedance/hybrid control based approaches, suggesting the ability to satisfy the cycle time requirement for industrial applications such as material handling.
Large block VQ for image sequences

Rate distortion theory indicates that a well-defined signal source can be compressed closely to the rate distortion bound, provided that the coding block length is large enough. This is the motivation of vector quantization (VQ) that quantizes a group of signals together as a vector. However, due to its exponentially increasing computational complexity, in the application area of image/video processing almost all unconstrained VQ work has been constrained to a vector size of 4×4. As the computer becomes much faster, it becomes computationally affordable to increase this standard vector dimension. The authors investigate the effect on VQ performance when the vector dimension is increased. Experimental results show that a significant improvement can be achieved by increasing the vector dimension from 4×4 to 8×8. Both the PSNR and visual performance are improved by increasing the vector dimension, but the computational complexity and codebook overhead both increase exponentially. Several algorithms have been tested to reduce the computation and a new approach to reduce the codebook overhead has been developed. Experiments show that both the computational complexity and the codebook overhead can be reduced significantly without losing much performance. Also, a new coding scheme-large block VQ with shift-is introduced as a way to improve the performance further.
Improving loadpull measurement time by intelligent measurement interpolation and surface modeling techniques

In this paper we show how a thin-plate spline approximation can be used to generate a model of the measured response surface of a load-pull measurement over a much-reduced number of impedance points with no significant loss of accuracy. Further, interpolation between these model surfaces is possible, generating accurate drive-up characteristics. This has enabled accurate load-pull characterizations to be made in a fraction of the usual time.
Memory fading Volterra series model for high power infrastructure amplifiers

This paper presents a novel technique of adapting the generalized Volterra series behavioral model to describe, with improved accuracy, power amplifiers targeting cellular infrastructure applications. The generalized Volterra series is reformulated with respect to the discrete time domain to allow impendent specification of memory depth for each kernel. A memory fading concept is then adopted to align memory depth to increasing kernel order. The number of Volterra coefficients needed to represent a strong PA non-linearity are significantly reduced (to a manageable level), while retaining certain high order kernels essential for realizing exceptional model fidelity. Results show model residuals better than -60 dBc for single- and two-carrier WCDMA signals when applied to a 350W LDMOS Doherty power amplifier circuit.
Scalable high-definition video coding

Multiresolution, or scalable, video coding has emerged to be of great interest in the compression community. It has been recognized that many applications, such as, image database browsing, desktop computing, terrestrial broadcasting, and others, can benefit from multiresolution viewing of embedded data sets. In this paper we present a new three-dimensional subband coder which provides six different spatio-temporal resolutions of a video signal. Motion-compensated temporal filtering (MCTF) is used for temporal analysis. The encoding algorithm efficiently compresses the data from the six resolutions into a single bit-stream while removing data which is redundant across different resolutions. Our algorithm successfully merges spatial and temporal scalability without imposing restrictions on which of the six video resolutions can be decoded, while allowing optimal encoding of the video at each spatial and temporal resolution.
Digital pre-distortion of RF power amplifiers: progress to date and future challenges

In this paper we present a review of digital pre-distortion from its earliest implementations in a radio transmitter, to modern designs used in wireless infrastructure base-stations today. We shall outline the nonlinear effects and algorithmic approaches commonly adopted, including the adaptive techniques that are widely used. We also present some of the challenges and opportunities for DPD in the future, as signal bandwidths increase and modulation formats proliferate.
Preshaped trajectories for residual vibration suppression in payloads suspended from multiple robot manipulators

Several methods are available for generating input trajectories that eliminate residual vibrations for a variety of systems. These methods have been successfully applied to an assortment of both linear and non-linear situations. While multiple input systems have been addressed, the issue of developing residual vibration-suppressed input trajectories for cooperative manipulators has not been satisfactorily covered in the literature. This research focuses specifically on the problem of multiple cooperative manipulators working in conjunction to move a common payload. A method is determined by which multiple modes of residual vibration are suppressed, and an input trajectory is computed for dual manipulators which reduces residual vibrations by at least seventy-five percent.
Maximum minimal distance partitioning of the Z2 lattice

We study the problem of dividing the /spl Zopf//sup 2/ lattice into partitions so that minimal intra-partition distance between the points is maximized. We show that this problem is analogous to the problem of sphere packing. An upper bound on the achievable intra-partition distances for a given number of partitions follows naturally from this observation, since the optimal sphere packing in two dimensions is achieved by the hexagonal lattice. Specific instances of this problem, when the number of partitions is 2/sup m/, were treated in trellis-coded modulation (TCM) code design by Ungerboeck (1982) and others. It is seen that methods previously used for set partitioning in TCM code design are asymptotically suboptimal as the number of partitions increases. We propose an algorithm for solving the /spl Zopf//sup 2/ lattice partitioning problem for an arbitrary number of partitions.
Subband coding of images using vector quantization

A novel two-dimensional subband coding technique is presented that can be applied to images as well as speech. A frequency-band decomposition of the image is carried out by means of 2D separable quadrature mirror filters, which split the image spectrum into 16 equal-rate subbands. These 16 parallel subband signals are regarded as a 16-dimensional vector source and coded as such using vector quantization. In the asymptotic case of high bit rates, a theoretical analysis yields that a lower bound to the gain is attainable by choosing this approach over scalar quantization of each subband with an optimal bit allocation. It is shown that vector quantization in this scheme has several advantages over coding the subbands separately. Experimental results are given, and it is shown the scheme has a performance that is comparable to that of more complex coding techniques.