A statistical model for point-based target registration error with anisotropic fiducial localizer error

Error models associated with point-based medical image registration problems were first introduced in the late 1990s. The concepts of fiducial localizer error, fiducial registration error, and target registration error are commonly used in the literature. The model for estimating the target registration error at a position r in a coordinate frame defined by a set of fiducial markers rigidly fixed relative to one another is ubiquitous in the medical imaging literature. The model has also been extended to simulate the target registration error at the point of interest in optically tracked tools. However, the model is limited to describing the error in situations where the fiducial localizer error is assumed to have an isotropic normal distribution in R3. In this work, the model is generalized to include a fiducial localizer error that has an anisotropic normal distribution. Similar to the previous models, the root mean square statistic rms tre is provided along with an extension that provides the covariance Sigma tre. The new model is verified using a Monte Carlo simulation and a set of statistical hypothesis tests. Finally, the differences between the two assumptions, isotropic and anisotropic, are discussed within the context of their use in 1) optical tool tracking simulation and 2) image registration.     

Two ADPCM Algorithms with Widely Separated Error Recovery Times

Two adaptive differential pulse code modulation (ADPCM) algorithms are discussed that provide for transmitter-receiver resynchronization when used in a non-zero error rate digital transmission medium. Novel techniques are used in the algorithms (e.g., step-size bias) and in their extensive characterization (e.g., intermodulation distortion measurements).     

Collaborative mitigation of partial-time jamming on nonfading channels

We propose new collaborative reception techniques for use in the presence of a partial-time Gaussian jammer. Under the proposed techniques, a group of radios acts as a distributed antenna array by exchanging information that is then used to perform jamming mitigation. We propose two such jamming mitigation techniques that offer a tradeoff between performance and complexity. The results show that these techniques can allow communications in much more severe jamming conditions than when collaboration is not employed or when conventional collaboration techniques based on maximal-ratio combining are applied. Example scenarios with strong jamming show that three collaborating radios can reduce the frame error rate by more than two orders of magnitude over single-radio reception. In another scenario it is shown that a jammer must jam at least 75% of the transmitted symbols to produce an unacceptable frame error rate with three collaborating radios, but only 43% of the transmitted symbols if there is no collaboration.     

Reverse bias measurements of the photoluminescent efficiency of semiconducting organic thin films

Photoluminescent (PL) efficiency measurements are an essential component of the characterization of high efficiency organic light emitting devices. We demonstrate that a reverse bias technique for measuring PL efficiency possesses several advantages. Using a two-tone synchronous detection scheme, it is found that nonlinearities in the reverse bias photoresponse are a probe for the presence of charge transfer states that may confuse the interpretation of PL data. Compared to alternative techniques, reverse bias measurements are also relatively unaffected by photoinduced changes in material properties.     

Direction-of-arrival estimates in the presence of wavelength, gain,and phase errors

Direction-of-arrival (DOA) estimation using an array of sensors relies on an accurate characterization of the array manifold. In the absence of characterization errors, established techniques like MUSIC can be shown to perform well both theoretically and in simulation. However, in the presence of unknown sensor and/or source characteristics, the performance of most methods degrades significantly. We consider the problem of estimating gain and phase errors of an array of sensors whose physical positions are known. Our algorithm assumes that the gain and phase characteristics of the sensors are independent of DOA and employs multiple calibration sources with known DOA's. It differs from other algorithms in that the signal wavelengths are unknown. A least-squares formulation of the problem is then shown to be NP-complete, implying that an efficient solution is unlikely to exist. An implicit, enumerative technique is used to obtain the exact solution. For the special case of collinear sensors, we further show that an inherent ambiguity in the model prevents exact phase characterization unless the wavelength of one calibration source is assumed known. A theorem is presented relating the error in DOA to the difference between the assumed and true wavelengths of this calibration source. Simulation results are presented for both noncollinear and collinear arrays     

任意偏置点的电光调制器自动偏置控制方法

为了实现对双电极马赫-曾德尔电光调制器任意直流偏置点的自动偏置控制,采用在闭环控制基础上,引入一个可调移相器使不同直流偏置点处误差信号相同的方法,理论分析了可调移相器相移量与直流偏置相位的关系,仿真得到对于不同偏置点,当调制器直流偏置相位漂移达-0.15rad~0.08rad,移相器引入附加相位漂移-0.55rad~0.55rad时,经偏置控制后相位漂移被限制在-3.010-4rad~1.710-4rad范围内。结果表明,该方法有效实现了对电光调制器任意直流偏置点的自动偏置控制。     

Simplified calibration of single-plunge bipolar electrode array for field measurement during defibrillation

In an earlier study, the authors presented a calibration technique for a triaxial bipolar electrode array (EA) that used 72 data points collected during a global sweep of the electric field vector relative to the EA axes. Although necessary for the initial characterization of the EAs, this data requirement has to be significantly reduced for the technique to become a practical tool. Therefore, in the present study, an analysis is performed to determine the relation between the number of data points used in the calibration and the mean root-mean-square error. The analysis shows that 18 data points can produce results nearly identical to those obtained with the 72-point calibration, thus reducing the required amount of data fourfold.     

Low bias frequency domain SNR estimator using DCT in mobile fading channels

The authors analyze the cause of bias in a fast Fourier transform (FFT)-based frequency domain signal-to-noise ratio (SNR) estimator by deriving the upper bound of the bias. The analysis is then used to propose a new frequency domain estimator using discrete cosine transform (DCT), which has lower bias. In addition, a criterion is proposed for use when maximum Doppler frequency information is available; it is based on the derived upper bound and can be used to improve the mean squared error (MSE) performance of the proposed DCT-based estimator. Simulation results show that the proposed estimator reduces the MSE remarkably by diminishing the bias.     

MEMS加速度计混合误差标定补偿方案

针对微机电系统(MEMS)加速度计在实际使用过程中存在非正交零偏误差和温度漂移误差的问题,提出了一种混合误差标定补偿算法。算法通过分析加速度计温度与误差的关系,在不同温度区间下建立加速度计输出的误差模型,在每个温度区间采用十二位置校准法对加速度计的非正交零偏误差进行标定补偿,得到精确的零偏和刻度因子,同时采用最小二乘法拟合零偏和刻度因子与温度的一维关系函数,最终实现不同温度区间下的动态误差补偿。实验结果表明,本算法可使加速度计输出的精度提高1个数量级,补偿效果明显。     

Biorthogonal filterbanks and energy preservation property in imagecompression

The energy preservation property is among the most widely used properties of orthogonal transforms in image compression because the reconstruction error can be computed as the sum of the subband distortions. Thus, this is a key point in the use of efficient bit allocation techniques such as rate-distortion algorithms. Therefore, we study the nonorthogonality of biorthogonal filterbanks with reference to energy preservation from both theoretical and applicative points of view. We calculate the Riesz bounds as energy preservation bounds for filterbanks and discrete wavelet transforms, and then connect these results with the Riesz bounds of the related continuous wavelet transform. The simultaneous use of biorthogonal filterbanks and rate-distortion algorithms is then discussed as the issue of estimating the reconstruction error as an additive function of the subband distortion. We propose a weighted sum of the subband distortions as an estimate, whose accuracy is calculated by a wide range of experiments. This accuracy is shown to be correlated to the Riesz bounds of the filterbanks. We conclude that from this point of view, most of the usual biorthogonal filterbanks may be considered as nearly orthogonal.     

Binary halftone image resolution increasing by decision tree learning

This paper presents a new, accurate, and efficient technique to increase the spatial resolution of binary halftone images. It makes use of a machine learning process to automatically design a zoom operator starting from pairs of input-output sample images. To accurately zoom a halftone image, a large window and large sample images are required. Unfortunately, in this case, the execution time required by most of the previous techniques may be prohibitive. The new solution overcomes this difficulty by using decision tree (DT) learning. Original DT learning is modified to obtain a more efficient technique (WZDT learning). It is useful to know, a priori, sample complexity (the number of training samples needed to obtain, with probability 1 - delta, an operator with accuracy epsilon): we use the probably approximately correct (PAC) learning theory to compute the sample complexity. Since the PAC theory usually yields an overestimated sample complexity, statistical estimation is used to evaluate, a posteriori, a tight error bound. Statistical estimation is also used to choose an appropriate window and to show that DT learning has good inductive bias. The new technique is more accurate than a zooming method based on simple inverse halftoning techniques. The quality of the proposed solution is very close to the theoretical optimal obtainable quality for a neighborhood-based zooming process using the Hamming distance to quantify the error.     

Performance limitations and error calculations for parameter estimation

Error calculations cannot be carried out precisely when parameters are estimated which affect the observation nonlinearly. This paper summarizes the available approaches to studying performance and compares the resulting answers for a specific case. It is shown that the familiar Cramér-Rao lower bound on rms error yields an accurate answer only for large signal-to-noise ratios (SNR). For low SNR, lower bounds on rms error obtained by Ziv and Zakai give easily calculated and fairly tight answers. Rate distortion theory gives a lower bound on the error achievable with any system. The Barankin lower bound does not appear to give useful information as a computational tool. A technique for approximating the error can be used effectively for a large class of systems. With numerical integration, an upper bound obtained by Seidman gives a fairly tight answer. Recent work by Ziv gives bounds on the bias of estimators but, in general, these appear to be rather weak. Tighter results are obtained for maximum-likelihood estimators with certain symmetry conditions. Applying these techniques makes it possible to locate the threshold level to within a few decibels of channel signal-to-noise ratio. Further, these calculations can be easily carried out for any system.     

Design of low-error fixed-width modified booth multiplier

This paper presents an error compensation method for a modified Booth fixed-width multiplier that receives a W-bit input and produces a W-bit product. To efficiently compensate for the quantization error, Booth encoder outputs (not multiplier coefficients) are used for the generation of error compensation bias. The truncated bits are divided into two groups depending upon their effects on the quantization error. Then, different error compensation methods are applied to each group. By simulations, it is shown that quantization error can be reduced up to 50% by the proposed error compensation method compared with the existing method with approximately the same hardware overhead in the bias generation circuit. It is also shown that the proposed method leads to up to 35% reduction in area and power consumption of a multiplier compared with the ideal multiplier.     

Computing rigorous bounds to the accuracy of calibrated stereo reconstruction [computer vision applications]

The authors deal with the problem of computing rigorous bounds on the position of 3D points obtained by stereo triangulation when both the camera matrix and the coordinates of image points are affected by measurement errors. By 'rigorous bounds' it is meant that the true unknown 3D points are guaranteed to lie within the intervals computed by the method, with mathematical certainty. To this end, the calibration process is first modelled by assuming a bounded error in the localisation of the reference points in the image, then narrow intervals are computed for the entries of the camera matrix using numerical methods based on interval analysis. Finally, triangulation is applied to obtain cuboids that bound point coordinates. Two state-of-the-art methods were employed for the solution of linear systems of interval equations, namely Rump's and Shary's methods. It is concluded that a careful selection of numerical techniques allows the use of interval analysis as a tool for obtaining realistic bounds on the output error, even in the presence of significant errors in the input data.     

Positioning in WLAN environment by use of artificial neural networks and space partitioning

Short range wireless technologies such as wireless local area network (WLAN), Bluetooth, radio frequency identification, ultrasound and Infrared Data Association can be used to supply position information in indoor environments where their infrastructure is deployed. Due to the ubiquitous presence of WLAN networks, positioning techniques in these environments are the scope of intense research. In this paper, the position determination by the use of artificial neural networks (ANNs) is explored. The single ANN multilayer feedforward structure and a novel positioning technique based on cascade-connected ANNs and space partitioning are presented. The proposed techniques are thoroughly investigated on a real WLAN network. Also, an in-depth comparison with other well-known techniques is shown. Positioning with a single ANN has shown good results. Moreover, when utilising space partitioning with the cascade-connected ANNs, the median error is further reduced for as much as 28%.     

Adaptive nonuniform phase-shift-key modulation for multimediatraffic in wireless networks

The characteristics of mobile wireless communication channels fluctuate for many reasons, including movement of the radios, changes in path attenuation, and variations in interference. Several adaptive signaling techniques have been proposed for use in wideband code-division multiple-access (CDMA) systems including adaptive data rates, adaptive spreading code rates, discontinuous transmission, and multicode CDMA. We introduce adaptive signaling techniques that use nonuniform phase-shift-key (PSK) modulation. These techniques have several advantages for use in CDMA communications, and they support multimedia transmission by simultaneously delivering different types of traffic, each with its own required quality of service. The signaling methods that we propose deliver a basic message at a specified error rate and simultaneously deliver an additional message by exploiting any extra capability that is available. We show that by adapting the location of the points in a PSK constellation, the throughput can be maximized for the additional message while maintaining an acceptable error rate for the basic message. Responses to larger changes in channel quality are accomplished by adapting the PSK constellation size, signaling rate, and error-correcting code. Examples of adaptive signaling schemes that employ nonuniform PSK constellations are presented, including an application to a cellular CDMA system     

Efficient algorithms for burst error recovery using FFT and othertransform kernels

We show that the problem of signal reconstruction from missing samples can be handled by using reconstruction algorithms similar to the Reed-Solomon (RS) decoding techniques. Usually, the RS algorithm is used for error detection and correction of samples in finite fields. For the case of missing samples of a speech signal, we work with samples in the field of real or complex numbers, and we can use FFT or some new transforms in the reconstruction algorithm. DSP implementation and simulation results show that the proposed methods are better than the ones previously published in terms of the quality of recovered speech signal for a given complexity. The burst error recovery method using the FFT kernel is sensitive to quantization and additive noise like the other techniques. However, other proposed transform kernels are very robust in correcting bursts of errors with the presence of quantization and additive noise     

Comparative study of AlGaN/GaN HEMTs robustness versus buffer design variations by applying Electroluminescence and electrical measurements

By means of step stressing tests on AlGaN/GaN HEMTs the robustness properties of devices fabricated on wafers with different buffer designs have been compared to each other (standard UID GaN buffer and UID Al_0.05Ga_0.95N back-barrier in combination with GaN channel layer). The devices with GaN buffer showed an abrupt increase of gate leakage current after reaching drain bias values in the range of 30 V while devices with Al_0.05Ga_0.95N back-barrier did not show any degradation up to 120 V drain bias. All DC-Step-Stress tests have been accompanied by Electroluminescence (EL) analysis and electrical characterization techniques before, during and after stress. It has been shown that EL at forward and reverse bias conditions can be used as an indicator of potential device degradation. Devices comprising an AlGaN back-barrier design demonstrated superior robustness.     

Location-quality-aware policy optimisation for relay selection in mobile networks

Relaying can improve the coverage and performance of wireless access networks. In presence of a localisation system at the mobile nodes, the use of such location estimates for relay node selection can be advantageous as such information can be collected by access points in linear effort with respect to number of mobile nodes (while the number of links grows quadratically). However, the localisation error and the chosen update rate of location information in conjunction with the mobility model affect the performance of such location-based relay schemes; these parameters also need to be taken into account in the design of optimal policies. This paper develops a Markov model that can capture the joint impact of localisation errors and inaccuracies of location information due to forwarding delays and mobility; the Markov model is used to develop algorithms to determine optimal location-based relay policies that take the aforementioned factors into account. The model is subsequently used to analyse the impact of deployment parameter choices on the performance of location-based relaying in WLAN scenarios with free-space propagation conditions and in an measurement-based indoor office scenario.