Parameter sensitivity of narrow-channel MOSFET's

An analytical method is used to examine the threshold voltage sensitivity due to various device parameter fluctuations in the narrow-channel MOSFETs. The analysis is based on a narrow-channel model with a semirecessed field-isolation structure and a short-channel modification. The results show that while the dopant-concentration and fixed-oxide charges fluctuation increases sensitivity, the back-gate bias fluctuation decreases sensitivity as the channel width is reduced. The present strategy is simple and is therefore ideal for miniaturized device processing simulation     

Parameter estimation using sensitivity points: tutorial andexperiment

Presented in this paper are a tutorial and experimental results for an iterative offline parameter identification scheme. The scheme utilizes the concept of sensitivity points to generate the gradient information that is used in the steepest descent estimation method. An experiment is conducted to identify parameters of a motor drive system in which the motor and load are connected by a compliant element. Estimated parameter values are also used in a position control experiment in which measured and designed responses are compared     

Parameter sensitivity of covariance-based response surfaces formodeling IC processes

When modeling the results of computer experiments which do not suffer from random errors, it is desirable that the models used exactly reproduce all the simulated data points. This paper discusses a method that ensures this and examines how small variations of the estimated parameters of the model influence the accuracy of the prediction. These findings are used to justify a procedure whereby the conditioning difficulties inherent in the method can be overcome     

Parameter sensitivity of MRAC models employed in IFO-controlled ACmotor drive

An investigation of the parameter sensitivities of the d-axis voltage, q-axis voltage, and the reactive power models used in model reference adaptive control (MRAC) strategy for tuning the indirect field-oriented (IFO) controller is presented. These reference models are derived from the dynamic model of the machine under the assumption that the IFO control conditions are valid. In this paper, the machine has been considered to operate under variable speed and load conditions. To improve the robustness of the MRAC strategy, a cascade parameter estimation technique has been used to track the variations in r_s and σl_s. The experimental results obtained with the proposed estimation technique, as well as with the MRAC strategy, are presented     

Some possibilities of indirect determination of network-function sensitivity to the ideal voltage-amplifier amplification

The sensitivity of network functions of a circuit containing an ideal voltage amplifier to the amplification-factor variation of this element is expressed with the help of various auxiliary network functions determined in the original circuit or in the circuit from which the ideal voltage amplifier was removed. The procedure is suitable for practical sensitivity measurements.     

A review of parameter sensitivity and adaptation in indirect vectorcontrolled induction motor drive systems

The effects of parameter sensitivity on indirect vector control induction motor drives are reviewed. The importance of parameter adaptation is discussed and categorized based on the extent of use of the induction motor parameters. The parameter sensitivity and compensation study is important from the point of view of optimum motor and power converter use. The scope for future research and some of the subsets of parameter compensation research are identified, and a detailed survey of the literature available in this topic is given     

Parameter sensitivity of soil moisture retrievals from airborne L-band radiometer measurements in SMEX02

Over the past two decades, successful estimation of soil moisture has been accomplished using L-band microwave radiometer data. However, remaining uncertainties related to surface roughness and the absorption, scattering, and emission by vegetation must be resolved before soil moisture retrieval algorithms can be applied with known and acceptable accuracy using satellite observations. Surface characteristics are highly variable in space and time, and there has been little effort made to determine the parameter estimation accuracies required to meet a given soil moisture retrieval accuracy specification. This study quantifies the sensitivities of soil moisture retrieved using an L-band single-polarization algorithm to three land surface parameters for corn and soybean sites in Iowa, United States. Model sensitivity to the input parameters was found to be much greater when soil moisture is high. For even moderately wet soils, extremely high sensitivity of retrieved soil moisture to some model parameters for corn and soybeans caused the retrievals to be unstable. Parameter accuracies required for consistent estimation of soil moisture in mixed agricultural areas within retrieval algorithm specifications are estimated. Given the spatial and temporal variability of vegetation and soil conditions for agricultural regions it seems unlikely that, for the single-frequency, single-polarization retrieval algorithm used in this analysis, the parameter accuracy requirements can be met with current satellite-based land surface products. We conclude that for regions with substantial vegetation, particularly where the vegetation is changing rapidly, any soil moisture retrieval algorithm that is based on the physics and parameterizations used in this study will require multiple frequencies, polarizations, or look angles to produce stable, reliable soil moisture estimates.     

Parameter sensitivity of soil moisture retrievals from airborne C- and X-band radiometer measurements in SMEX02

Among passive microwave frequencies, sensors operating at C- and X-band frequencies have been used with some success to estimate near-surface soil moisture from aircraft and satellite platforms. The objective of this paper is to quantify the sensitivities of soil moisture retrieved via a single-channel single-polarization algorithm to the observed brightness temperature and to retrieval algorithm parameters of surface roughness, vegetation B parameter, and single-scattering albedo. Examination of the regions within the parameter space that produce accurate soil moisture retrievals reveals that reasonably accurate retrievals can be made over a range of conditions using a fixed set of input parameters. Retrievals with horizontally polarized brightness temperature observations are more consistent than with vertically polarized observations. At horizontal polarization, sensitivity to the input parameters is much greater for wet soils than for dry soils, whereas for vertical polarization the moisture dependence is much weaker. At vertical polarization, sensitivities to variations in all parameters are much lower. To ensure that retrieval accuracy specifications are consistently met, high soil moisture conditions should be used in defining parameter accuracy requirements. Given the spatial and temporal variability of vegetation and soil conditions, it seems unlikely that, for regions with substantial rapidly growing vegetation, the accuracy requirements for model parameters in a single-frequency, single-polarization retrieval algorithm can be met with current satellite products. For such conditions, any soil moisture retrieval algorithm using parameterizations similar to those of this study may require multiple frequencies, polarizations, or look angles to produce stable, reliable soil moisture estimates.     

万有斥力定律

但上式仅适用于弱引力场,对强引力场就会失效,譬如由上式可推出物体可无限制地向黑洞中心集中,但实际上这显然是不可能的.为了克服广义相对论的这一根本弱点,必须考虑运动体的狭义相对论效应.狭义相对论表明:在两个互作匀速运动的物体上时空会发生“尺缩”、“钟慢”等一系列深刻的时空变化.虽然在重力场作用之下的物体是加速运动,但它的每一瞬间都可看作是匀速运动.这必然会导致重力场中运动体的时间改变.由此可推得重力场中精确的线元函数应为     

Simplistic universal coding

A conceptually simple coding method may be described as follows. The source sequence is parsed into fixed-length blocks and a list of these blocks is placed in a dictionary. In the lossless case, the dictionary is transmitted and each successive block is encoded by giving its dictionary location. In the lossy case, the smallest collection of blocks such that every member of the dictionary is within distortion δ of the collection is determined, this codebook is transmitted, and each successive block is encoded by giving the location of a member of the code within δ of it. We show that by optimizing on the block length, this method is universal, that is, for any ergodic process it achieves entropy in the limit in the lossless case and the rate-distortion function R(δ) in the lossy case     

The universal handset

Software-defined radio can let cellphones speak Wi-Fi, 3G, WiMax, and more. In the new millennium, SDR has spread from the battlefield to the commercial arena. Wireless service providers, in particular, have begun using it in the transceivers in cellphone base stations, allowing the same hardware to handle different cellular protocols. Next, SDR will spread to sets that fit in the palm of your hand. A mobile software radio that could communicate in all of these ways would, of course, be invaluable. Up until now, SDR technology worked only in applications that didn't need to be small in size or frugal in power consumption. New technology should, however, overcome these constraints. Indeed, within the next year or so, you can expect to see people moth- balling their old cellphones in favor of new software- defined handsets.     

On universal quantization

The quantization ofn-dimensional vectors inR^{n}with an arbitrary probability measure, under a mean-square error constraint, is discussed. It is demonstrated that a uniform, one-dimensional quantizer followed by a noiseless digital variable-rate encoder ("entropy encoding") can yield a rate that is, for anyn, no more than0.754bit-per-sample higher than the rate associated with the optimaln-dimensionai quantizer, regardless of the probabilistic characterization of the inputn-vector for the allowable mean-square error.     

Hierarchical universal coding

In an earlier paper, we proved a strong version of the redundancy-capacity converse theorem of universal coding, stating that for “most” sources in a given class, the universal coding redundancy is essentially lower-bounded by the capacity of the channel induced by this class. Since this result holds for general classes of sources, it extends Rissanen's (1986) strong converse theorem for parametric families. While our earlier result has established strong optimality only for mixture codes weighted by the capacity-achieving prior, our first result herein extends this finding to a general prior. For some cases our technique also leads to a simplified proof of the above mentioned strong converse theorem. The major interest in this paper, however, is in extending the theory of universal coding to hierarchical structures of classes, where each class may have a different capacity. In this setting, one wishes to incur redundancy essentially as small as that corresponding to the active class, and not the union of classes. Our main result is that the redundancy of a code based on a two-stage mixture (first, within each class, and then over the classes), is no worse than that of any other code for “most” sources of “most” classes. If, in addition, the classes can be efficiently distinguished by a certain decision rule, then the best attainable redundancy is given explicitly by the capacity of the active class plus the normalized negative logarithm of the prior probability assigned to this class. These results suggest some interesting guidelines as for the choice of the prior. We also discuss some examples with a natural hierarchical partition into classes     

A universal prediction lemma and applications to universal datacompression and prediction

A universal prediction lemma is derived for the class of prediction algorithms that only make inferences about the conditional distribution of an unknown random process based on what has been observed in the training data. The lemma is then used to derive lower bounds on the efficiency of a number of universal prediction and data compression algorithms. These bounds are nonasymptotic in the sense that they express the effect of limited training data on the efficiency of universal prediction and universal data compression     

The performance of universal encoding

Universal coding theory is surveyed from the viewpoint of the interplay between delay and redundancy. The price for universality turns out to be acceptably small.     

Voltage-mode FDCCII-based universal filters

Three new voltage-mode universal biquadratic filters configuration are proposed. The first proposed high-input impedance universal filter with single input and five outputs, which can simultaneously realize voltage-mode lowpass (LP), bandpass (BP), highpass (HP), bandstop (BS) and allpass (AP) filter responses employing all grounded passive components. The second proposed high-input impedance universal filter with three input and single output, which also can realize all the standard filter functions without requiring any inverting input voltage signal. The third proposed universal filter with three inputs and five outputs, which can be used as either a three-input single-output or a two-input five-output universal filter. Moreover, each of the proposed circuits still enjoys (i) the employment of only grounded capacitors, and (ii) no requirement with the component choice conditions to realize specific filtering functions.     

Rectangular universal iterative array

A rectangular universal iterative array consisting of cells having three inputs and one output is described. This array achieves the best known rate of increase in area.     

A self-adaptive universal receiver

In this paper we describe a new Self-Adaptive Re-Configurable Terminal, based on blind recognition of the system in use. This new terminal is operates thanks to a new radio interface receiver concept comprising two functional phases. These two phases are mapped on a specific architecture previously presented in [1]. The first one is devoted to a Wide Band Analysis (Wba) of the received signal in order to find which standard is being used. The second one being the demodulation itself. In this paper we focus on thisWba. It includes an iterative process in order to find the right bandwidth which has to be compatible with the Signal Processing techniques we use. During the last step of the process, blind standard recognition is performed by means of Radial Basis Function Neural Networks, which allow making full use of the analogy between our problem and conventional pattern recognition problems. Extensive simulation with true data of signals received in our lab has been performed and confirms the interest and efficiency of this type of recognition.     

Weighted universal image compression

We describe a general coding strategy leading to a family of universal image compression systems designed to give good performance in applications where the statistics of the source to be compressed are not available at design time or vary over time or space. The basic approach considered uses a two-stage structure in which the single source code of traditional image compression systems is replaced with a family of codes designed to cover a large class of possible sources. To illustrate this approach, we consider the optimal design and use of two-stage codes containing collections of vector quantizers (weighted universal vector quantization), bit allocations for JPEG-style coding (weighted universal bit allocation), and transform codes (weighted universal transform coding). Further, we demonstrate the benefits to be gained from the inclusion of perceptual distortion measures and optimal parsing. The strategy yields two-stage codes that significantly outperform their single-stage predecessors. On a sequence of medical images, weighted universal vector quantization outperforms entropy coded vector quantization by over 9 dB. On the same data sequence, weighted universal bit allocation outperforms a JPEG-style code by over 2.5 dB. On a collection of mixed test and image data, weighted universal transform coding outperforms a single, data-optimized transform code (which gives performance almost identical to that of JPEG) by over 6 dB.     

Current-mode active-only universal filter

A novel current-mode active-only universal filter based on and employing three DO-CCCIIs and two OAs is introduced. The circuit is fully integrable and programmable, and implements all the five generic filtering functions. The three basic filtering responses LP, BP and HP are implemented simultaneously by the circuit, while AP and notch signals can be realized simply by connecting appropriate node currents. The currents are available at high output impedances, so the synthesized filter can be cascaded without additional buffers to realize higher order filters. The filter performance factors ω ₀ and Q are electronically tunable in an orthogonal manner through separate bias currents of the CCCII. The PSPICE simulation was carried out to realize the proposed circuit.