nils-herrmann/clean_scirepeval huggingface dataset:
The Evolution of PA Linearization: From Classic Feedforward and Feedback Through Analog and Digital Predistortion

This article reviews the history and concepts behind the linearizers in use today. Predistortion linearization is by far the most widely used form of linearization and is most commonly generated digitally (DPD) for use in telecommunications and relatively limited bandwidth applications. The future for DPD looks bright, with new developments in software and hardware and exciting opportunities for disruptive approaches to be successful. For wider bandwidths, analog predistortion is often used. Rapid progress is being made to produce linearizers of very wide bandwidth and to extend their capabilities to the upper millimeter-wave bands. Multi-octave analog predistorters with greater than 10 GHz of bandwidth and that operate to 100 GHz have been produced.
Compound Gauss-Markov random fields for image estimation

Algorithms for obtaining approximations to statistically optimal estimates for images modeled as compound Gauss-Markov random fields are discussed. The authors consider both the maximum a posteriori probability (MAP) estimate and the minimum mean-squared error (MMSE) estimate for image estimation and image restoration. Compound image models consist of several submodels having different characteristics along with an underlying structure model which govern transitions between these image submodels. Two different compound random field models are employed, the doubly stochastic Gaussian (DSG) random field and a compound Gauss-Markov (CGM) random field. The authors present MAP estimators for DSG and CGM random fields using simulated annealing. A fast-converging algorithm called deterministic relaxation, which, however, converges to only a locally optimal MAP estimate, is also presented as an alternative for reducing computational loading on sequential machines. For comparison purposes, the authors include results on the fixed-lag smoothing MMSE estimator for the DSG field and its suboptimal M-algorithm approximation.
An Investigation of Computerized Tomography by Direct Fourier Inversion and Optimum Interpolation

In this paper an exact interpolation formula forms the basis for reconstructing computerized tomographic (CT) imagery by direct Fourier methods. Practical variations of exact interpolation are compared with other interpolation methods (i.e., nearest neighbor, etc.) and are shown to yield superior imagery. Images produced by the direct Fourier approach using near-exact interpolation are shown to be equal in quality with those produced by filtered convolution backprojection (FCBP). Moreover, the direct Fourier approach computes an image in O(N2 log N) time versus O(N3) for the FCBP method.
Simulating asynchronous architectures on transputer networks

Recently, there has been a resurgence of interest in asynchronous design techniques due to the potential of asynchronous logic for higher performance, power efficiency and immunity from clock related timing problems. Occam, a CSP based parallel language provides for the rapid development of asynchronous architectural simulation models which may then be executed on a transputer network to achieve high performance. The paper discusses issues related to the design and execution of such models.
Genetic algorithm for inter-frame region object temporal correlation in binary partition tree

Video contains rich information in the spatial and temporal domains. A single video shoot consists of a number of frames which are generally composed of similar objects which may have changed in position and size. The ability to recognize regions in the current frame is an important task in video analysis, but their subsequent recognition in the next frame receives little attention. This research utilizes a region based binary partition tree (BPT) as the content representation; object searching is conducted inside the binary tree and not in the original pixel domain. This work was conceived from the postulate: If an object exists inside a binary tree partition for a given video frame, can a corresponding branch be found in the BPT of the next frame? This is a difficult problem with a one to many and a many to one mapping and requires an innovative solution in the form of a Genetic algorithms (GA). GA's are ideally suited to this problem as the start and end conditions are known. This research proposes and achieves temporal correlation in region based BPTs using a genetic algorithm.
Semi-automatic BPT for Image Retrieval

This paper presents a novel semi-automatic tool for content retrieval. A multi-dimension Binary Partition Tree (BPT) is generated to perform object based image retrieval. The tree is colour based but has the advantage of incorporating spatial frequency to form semantically meaningful tree nodes. For retrieval, a node of the query image is matched against the nodes of the BPT of the database image. These are matched according to a combination of colour histograms, texture features and edge histograms. This semi-automatic tool allows users to have more freedom in their choice of query. The paper illustrates how the use of multi-dimensional information can significantly enhance content retrieval results for natural images.
Sensitivity of model-based coded video to packet losses

Previous model-based video coding studies have focused on the modelling techniques themselves and have not considered the transportation of an implementable coder over lossy networks. In this article a hybrid switched 3D model-based/H.261 video coder designed for one-to-many distance learning applications over the Internet multicast backbone (MBONE) is employed to study the susceptibility to data loss of model based packet video. Data is considered as; texture, motion and shape, with further sub-division to periodic and aperiodic types. The absence of the various data streams in isolation is investigated to reveal the types of degradation possible and then statistical loss is applied to all streams simultaneously to observe the combined effects using a simple loss model. The ability of the various streams to recover from these errors is investigated and an order of priority for the data types is then identified.
Time-varying analysis of autonomic control in response to spontaneous sighs in sickle cell anemia

Sickle cell anemia (SCA) is a genetic disease which is characterized by painful episodes of vascular occlusions. In the present study, we investigated a potential contribution of the autonomic nervous system (ANS) in initiating such episodes. We observed prominent decreases in microvascular perfusion in response to spontaneous sighs, which may increase the likelihood of red blood cell polymerization followed by vascular occlusions in SCA patients. Time-varying spectral analysis of heart rate variability (HRV), based on recursive least squares estimation, was employed to study the modulation of the ANS in response to sighs. To improve robustness of the spectral estimation while retaining its ability to track rapid changes, we propose a time-varying parameter estimate variability reduction (TV-PEVR) technique. Because respiration patterns can vary considerably across subjects, we employed a time-varying autoregressive with exogenous input (TV-ARX) model to adjust for the effect of respiration patterns on the HRV indices. Results from 8 SCA subjects and 9 normal controls suggested that the cardiac ANS responses to sighs are not different between the two groups, after adjusting for the effect of post-sigh respiration. However, the peripheral sympathetic response in SCA appeared to be enhanced in this group relative to normals, and sighs may play a role in initiation of vaso-occlusive events in this group of patients.
The deterioration of mica under the action of electrical discharges

This paper describes an investigation into the discharge resistance of high grades of Muscovite and Phlogopite micas. Internal discharge experiments have been performed in air at NTP with electric stress up to 8 kV mm-1with a frequency acceleration factor of 24. The samples were not tested to breakdown but examined at selected times up to an equivalent period of ten years at power frequency. Both types of mica experienced a similar pattern of deterioration starting with a surface crazing and the development of minute nodules. With continued discharge attack the crazed surface began to peel exposing newly cleaved surfaces which subsequently, repeated the peeling effect, resulting in puncture of the flake at the centre of these areas. During this development initially curled flakes and surface nodules develop dendritic formations modifying the electric stress and enhancing the discharge attack. Micro-probe analyses of the surfaces and surface products at various stages of degradation indicated that depletion and removal of the metallic cations had occurred in the micas resulting in a collapse of their crystalline stability and the formation of silica. The lost cations were found present as metallic salts in solution and solidified residues on the mica surfaces.
Time-frequency analysis of the first heart sound

Quantitative phonocardiography has been limited by many factors: nonstandard nomenclature and recording techniques, complicated mechanoacoustic generation, propagation and coupling, and inherent heart sound nonstationarity. New nonstationary signal processing techniques provide a powerful tool for phonocardiography, particularly in regard to the first heart sound. Recent work supports the concept that the first heart sound is composed of valve-initiated myocardial traveling waves superimposed upon the acceleration of myocardial contraction. Clinically, nonstationary signal analysis has been most frequently applied toward the study of mechanical prosthetic valves. However, a better understanding of first heart sound mechanics may facilitate the diagnosis of myocardial and native-valve pathology. Given the inherent system complexity, an interdisciplinary approach incorporating physicians, mechanical engineers, seismologists, and electrical engineers is imperative.
Inward nonlinear characterization of Doherty Power Amplifiers

Doherty technique is widely sought for power efficiency enhancement through proper built-in load modulation. However, its implementation still lacks appropriate tools for detecting the sources of discrepancies between the simulated and measured performance. In this paper, a time-domain characterization technique is used to capture the individual nonlinear characteristics of the main and auxiliary amplifiers of a given Doherty Power Amplifier (DPA). This technique helped identify a significant input power dependent phase mismatch between the two amplifiers that was found to contribute to the overall distortions. Contrary to conventional characterization techniques, the inward characterization allows for capturing internal measurements data that provides insights on the operation of the DPA's building blocks and its troubleshooting.
Behavioral modeling and digital predistortion of Power Amplifiers with memory using Two Hidden Layers Artificial Neural Networks

This paper presents a novel Two Hidden Layers Artificial Neural Networks (2HLANN) model for behavioral modeling and linearization of RF Power Amplifiers (PAs). Starting with a feedback loop principle model of a PA, an appropriate neural networks structure is deduced. This structure was then optimized to form a real valued and feed-forward 2HLANN based model capable of predicting the nonlinear behavior and the memory effects of wideband PAs. The validation of the proposed model in mimicking the behavior of a Device Under Test (DUT) is carried out in terms of its accuracy in predicting the output spectrum, dynamic AM/AM and AM/PM characteristics and the normalized mean square error. In addition, the 2HLANN model was used to linearize two 250 Watt peak-envelope-power Doherty PAs (DPAs) driven with 20 MHz bandwidth signals. The linearization of these DPAs using the 2HLANN enabled attaining an output power of up to 46.8 dBm and an average efficiency of up to 47.5% coupled with an Adjacent Channel Power Ratio higher than 50 dBc. When compared to a number of previously published behavioral and DPD schemes, the 2HLANN model demonstrated an excellent modeling accuracy and linearization capability.
A Quasi-Two-Dimensional Model for High-Power RF LDMOS Transistors

A new quasi-2-D model for laterally diffused metal-oxide-semiconductor radio-frequency power transistors is described in this paper. We model the intrinsic transistor as a series laterally diffused p-channel and n-type drift region network, where the regional boundary is treated as a reverse-biased p+-n diode. A single set of 1-D energy transport equations is solved across a 2-D cross section in a “current-driven” form, and specific device features are modeled without having to solve regional boundary node potentials using numerical iteration procedures within the model itself. This fast process-oriented nonlinear physical model is scalable over a wide range of device widths and accurately models direct-current and microwave characteristics.
Radon transformation of time-frequency distributions for analysis of multicomponent signals

The Radon transform of a time-frequency distribution produces local areas of signal concentration that facilitate interpretation of multicomponent signals. The Radon-Wigner transform can be efficiently implemented with dechirping in the time domain, however, only half of the possible projections through the time-frequency plane can be realized because of aliasing. We show here that the frequency dual to dechirping exists, so that all of the time-frequency plane projections can be calculated efficiently. Both time and frequency dechirping are shown to warp the time-frequency plane rather rotating it, producing an angle dependent dilation of the Radon-Wigner projection axis. We derive the discrete-time equations for both time and frequency dechirping, and highlight some practical implementation issues. Discrete dechirping is shown to correspond to line integration through the extended-discrete, rather than the discrete, Wigner-Ville distribution. Computationally, dechirping is O(2N log 2N) instead of O(N/sup 3/) for direct projection, and the computation is dominated by the fast Fourier transform calculation. The noise and cross-term suppression of the Radon-Wigner transform are demonstrated by several examples using dechirping and using direct Radon-Wigner transformation.
A Cooperative Heterogeneous Mobile Wireless Mechatronic System

This paper describes a framework for controlling a heterogeneous wireless robotic network consisting of aerial and ground vehicles. By use of the term heterogeneous, we imply the synergy of multiple robotic platforms characterized by different dynamics and specialized sensing capabilities. Two main scenarios concerning wireless communications are presented: 1) a decentralized connectivity strategy in which a mesh of ground mobile routers swarms in a cluttered environment maintaining communication constraints based on spring-mass virtual physics, potential functions, and routing optimization and 2) an autonomous communications relay in GPS-denied environments via antenna diversity and extremum-seeking SNR optimization. For both scenarios, we validate the proposed methodologies by numerical simulations and experiments. One important feature of our test bed is that it can be used for both indoor and outdoor operations.
Two-dimensional processing of spectrogram data

In this paper we demonstrate a new application of two-dimensional (2-D) signal processing. The 2-D data consists of frequency-time plots or spectrograms derived from non-stationary one-dimensional data. We show that 2-D processing can offer significant advantages over the standard spectral estimation procedures used to obtain spectrograms. These advantages mainly occur because the frequency data is correlated in time, a fact ignored in conventional spectrogram procedures. Recursive fan type filters are designed by the homomorphic method and applied to the spectrogram data. Significant improvement is obtained for a simulation consisting of chirp type signals in white noise.
Special delivery: An increase in MMS adoption

This article is aimed at identifying thconsumer'se additional factors that are not considered by the research communities in addressing the problems affecting the growth of MMS in a mobile network. The technocommercial issues are highlighted and a solution is proposed that is technically feasible and commercially acceptable. The main contribution is in highlighting the drawbacks of the current delivery mechanism where users are unable to evaluate the content before downloading an MMS message. In the cunent mechanism, the different parts of an MMS message (including audio, video, and image) are transcoded in the MMS center to make the contents presentable to heterogeneous types of mobile handsets. We show that with the delivery of a summary of the contents, the consumer's acceptability to MMS can be potentially improved. The proposed change in the delivery process, which considers the dynamic situation of the handset, will enhance the MMS presentation and improve the level of satisfaction. The change will enable the operator to divide the charge between the sender and receiver and also to exploit the asymmetry in utility gained.
Two-dimensional discrete Markovian fields

A definition of discrete Markovian random fields is formulated analogously to a definition for the continuous case given by Levy. This definition in the homogeneous Gaussian case leads to a difference equation that sets forth the state of the field in terms of its values on a band of minimum width P , where P is the order of the process. The state of the field at position (i,j) is given by the set of values of the nearest neighbors within distance P of the point (i,j) . Conversely, given a difference equation satisfying certain conditions relating to stability, there corresponds a homogeneous discrete Markov random field. This theory is applied to the problem of obtaining spectral estimates of a two-dimensional field, given observation over a limited aperture.
Two-dimensional spectral factorization with applications in recursive digital filtering

The concept of spectral factorization is extended to two dimensions in such a way as to preserve the analytic characteristics of the factors. The factorization makes use of a homomorphic transform procedure due to Wiener. The resulting factors are shown to be recursively computable and stable in agreement with one-dimensional (1-D) spectral factorization. The factors are not generally two-dimensional (2-D) polynomials, but can be approximated as such. These results are applied to 2-D recursive filtering, filter design, and a computationally attractive stability test for recursive filters.
The behavioral modeling of microwave/RF ICs using non-linear time series analysis

A new and powerful, systematic approach for creating nonlinear behavioral models of microwave/RF ICs is presented. The methodology incorporates several techniques from nonlinear dynamics, system identification, and computational geometry to produce models that are an effective compromise between complexity and accuracy, and efficiency and speed of simulation. The models are constructed from large-signal microwave measurements in the time domain, or from simulation, and are implemented in a commercial nonlinear microwave simulator. We illustrate the technique by creating a cascadable, transportable model of a microwave IC amplifier that predicts accurately the DC, large signal, harmonic distortion, inter-modulation, and small-signal S-parameter behavior.
A parallel identification procedure for images with noncausal symmetric blurs

In this paper a parallel scheme is presented for the identification of two-dimensional noncausal image blurs. It is shown that the blur identification problem can be specified as a parallel set of one-dimensional complex autoregressive moving average (ARMA) identification problems. By expressing the ARMA models as equivalent infinite-order auto-regressive (AR) models, an entirely linear estimation procedure can be followed yielding minimum phase solutions. Further, it will be shown that under certain conditions (blur symmetry) it is possible to reconstruct a useful noncausal set of MA (blur) parameters from the identified minimum-phase set. Several identification results are given as examples.
Time Frequency Transforms Of The Human First Heart Sound

The frequency dynamics of the human first heart sound were assessed at 27 locations across the human thorax using Reduced Interference time-frequency transforms. Time-frequency transformation demonstrated prominent impulse-like components in the superior thorax. In this region, signal dynamics were well described by the instantaneous power and the power spectrum. Spectra from the inferior thorax, however, revealed signal components whose frequency rose rapidly during the isovolumic contraction period. Statistics based upon the joint time-frequency spectrum, such as the instantaneous modal frequency, were necessary to capture heart sound frequency variation. These studies demonstrate that the externally recorded human first heart sound is a non-stationary signal and suggest that time-frequency transforms may be useful in relating human first heart sound frequency dynamics to the underlying vibrational mechanics.
Modification of GaAs Schottky barriers using a-Si:H interfacial layers

The electrical characteristics of metal/a-Si:H/n-GaAs diode structures were studied in order to investigate the role of the a-Si:H and the claim of no barrier at the GaAs/a-Si:H interface. Diodes were fabricated using a-Si:H layers between 30 and 1920 AA thick, with Al and Mg metallization, and the current-voltage and capacitance-voltage characteristics were examined. Rectifying Schottky barriers were formed at Al/a-Si:H junctions, while good ohmic contacts were formed at Mg/a-Si:H junctions, enabling effects due to the metal/a-Si:H and a-Si:H/GaAs interface to be isolated. A dramatic increase in the forward turn-on voltage was observed as the thickness of the a-Si:H layer increased. The diode behavior can be explained by considering three effects in series: (1) an a-Si:H/GaAs barrier of about 0.6 eV, consistent with Fermi-level pinning in GaAs; (2) a metal/a-Si:H barrier, dependent on the metallization; and (3) space-charge-limited current (SCLC) in the bulk a-Si:H. The SCLC effectively gives rise to a voltage-dependent resistance and causes the increased turn-on voltages.<<ETX>>
Fuzzy logic inference system-based hybrid quality prediction model for wireless 4kUHD H.265-coded video streaming

Networked visual applications such video streaming have grown exponentially in recent years, yet are known to be sensitive to network impairments. However, available measurement techniques that adopt a full reference model are impractical in real-time streaming because they require the original video sequence available at the receivers side. The primary aim of this study is to present a hybrid no-reference prediction model for the perceptual quality of 4kUHD H.265-coded video in the wireless domain. The contributions of this paper are two-fold: first, an investigation of the impact of quality of service (QoS) parameters on 4kUHD H.265-coded video transmission in an experimental environment; second, objective model based on fuzzy logic inference system is developed to predict the visual quality by mapping QoS parameters to the measured quality of experience. The model is evaluated in contrast to random neural networks. The results show that good prediction accuracy was obtained from the proposed hybrid prediction model. This study will help in the development of a reference-free video quality prediction model and QoS control methods for 4kUHD video streaming.