Subject-specific estimation of central aortic blood pressure using an individualized transfer function: a preliminary feasibility study

This paper presents a new approach to the estimation of unknown central aortic blood pressure waveform from a directly measured peripheral blood pressure waveform, in which a physics-based model is employed to solve for a subject- and state-specific individualized transfer function (ITF). The ITF provides the means to estimate the unknown central aortic blood pressure from the peripheral blood pressure. Initial proof-of-principle for the ITF is demonstrated experimentally through an in vivo protocol. In swine subjects taken through wide range of physiologic conditions, the ITF was on average able to provide central aortic blood pressure waveforms more accurately than a nonindividualized transfer function. Its usefulness was most evident when the subject's pulse transit time deviated from normative values. In these circumstances, the ITF yielded statistically significant reductions over a nonindividualized transfer function in the following three parameters: 1) 30% reduction in the root-mean-squared error between estimated versus actual central aortic blood pressure waveform (p < 10 (-4)), 2) >50% reduction in the error between estimated versus actual systolic and pulse pressures ( p < 10 (-4)), and 3) a reduction in the overall breakdown rate (i.e., the frequency of estimation errors >3 mmHg, p < 10 (-4)). In conclusion, the ITF may offer an attractive alternative to existing methods that estimates the central aortic blood pressure waveform, and may be particularly useful in nonnormative physiologic conditions.     

A model for radial yield degradation as a function of chip size

Yield data was collected from a total of 928 200-mm silicon wafers which were processed using a 1 μm CMOS technology. Each wafer was patterned with one of four chips varying in area from 17 mm² to 132 mm². Wafers with like chips were binned together into a single grand composite wafer for each of the four chip sizes. The yield was subsequently plotted as a function of radius, and a mathematical expression was empirically fitted to the radial yield plots. The coefficients from each of the fitted expressions were then used to form a generalized expression for radial yield degradation as a function of chip size. The method of normalization, and the algorithm used to generate the radial yield plots are discussed. An explanation of the data is offered based on geometrical considerations. The radial yield dependence is then incorporated into more traditional yield models     

A deterministic frequency-domain model for the indoor power line transfer function

The characterization of the transfer function of the power line (PL) channel is a nontrivial task that requires a truly interdisciplinary approach. Until recently, a common attribute and limitation of existing models for the PL channel transfer function lay in the phenomenological or statistical approach usually followed. This approach allows one to describe the channel only partially, e.g., as dominated by multipath-like effects, and prevents one from unveiling special properties of it. Multiconductor transmission line (MTL) theory was recently found by the authors to be a useful and accurate tool in modeling the PL transfer function while, at the same time, taking into account the wiring and grounding practices mandated by several regulatory bodies for commercial and residential premises. Crossing several layers of abstraction and following a bottom-up approach, complex circuit-level models originating from MTL theory can be manipulated and represented in terms of cascaded two-port networks (2PNs), thus allowing one to compute a priori and in a deterministic fashion the transfer function of any PL link. In the present contribution, we present additional analysis and data that validate the accuracy of the MTL approach and further justify its use in the PL channel context. Moreover, we also describe in detail the methodology to follow for modeling both grounded and ungrounded PL links in a unified framework. A consequence of the validity of the proposed modeling is that it can facilitate the process of standardization of the PL transfer function, an important step toward the availability of a commonly agreed upon (set of) channel transfer functions.     

Parametric shape representation by a deformable NURBS model for cardiac functional measurements

This paper proposes a method of parametric representation and functional measurement of 3-D cardiac shapes in a deformable nonuniform rational B-splines (NURBS) model. This representation makes it very easy to automatically evaluate the functional parameters and myocardial kinetics of the heart, since quantitative analysis can be followed in a simple way. In the model, local deformation and motion on the cardiac shape are expressed in adjustable parameters. Especially, an effective integral algorithm is used for volumetric measurement of a NURBS shape since the volume is the most basic parameter in cardiac functional analysis. This method promises the numerical computation to be very convenient, efficient, and accurate, in comparison with traditional methods. Practical experiments are carried out, and results show that the algorithm can get satisfactory measurement accuracy and efficiency. The parametric NURBS model in cylindrical coordinates is not only very suitable to fit the anatomical surfaces of a cardiac shape, but also easy for geometric transformation and nonrigid registration, and able to represent local dynamics and kinetics, and thus, can easily be applied for quantitative and functional analysis of the heart.     

Nonparametric regression estimation by normalized radial basis function networks

This paper establishes weak and strong universal consistency of regression estimates based on normalized radial basis function networks when the network parameters are chosen by empirical risk minimization.     

Minimal radial basis function neural networks for nonlinear channelequalisation

The results of linear and nonlinear channel equalisation in data communications are presented, using a previously developed minimal radial basis function neural network structure, referred to as the minimal resource allocation network (MRAN). The MRAN algorithm uses online learning, and has the capability to grow and prune the RBF network's hidden neurons ensuring a parsimonious network structure. Compared to earlier methods, the proposed scheme does not have to estimate the channel order first, and fix the model parameters. Results showing the superior performance of the MRAN algorithm for two linear channels (minimum and non-minimum phase) for 2PAM signalling, and three nonlinear channels for 2PAM and 4QAM signalling, are presented     

模型分析及测试方法计算大气调制传递函数

采用基于点扩散函数的模型分析和基于测试方法的MODTRAN计算两种方法,计算了大气调制传递函数。通过引入大气分层对调制传递函数的影响,给出一种大气折射率结构常数的综合计算方法,修正了大气调制传递函数模型,明确给出了模型中的参数及计算方法。利用MODTRAN软件计算大气调制传递函数的模型并给出了计算方法。以机载成像仪的工作环境为背景对模型进行了仿真分析,讨论了影响调制传递函数的因素,为评价大气对成像仪的影响提供了依据。     

Approximation of a sampled impulse-response function by a pulse transfer function

The method of moments is used to fit a pulse transfer function of given order r to a given sampled impulse-response function. By this means, the model correctly predicts the system response to an arbitrary polynomial input of order 2r?1, and correctly predicts the required polynomial input to correct for additive polynomial drift at the output of order 2r?1.     

1.5位pipelined ADC单级传函的数模分析

1.5位结构是构成pipelined ADC的基本单元,总结了2位向1.5位方案传函的演变过程,但对转换的最优性并未证明。在此通过理论分析揭示了ADC及其单级传输函数变换的本质,证明了在Pipeline结构中,ADC单级传输函数演变的本质是:通过单级传函的变化,使整个ADC最终的传输函数与我们所习惯使用的(或者说最初使用的),相差不大于1个LSB,同时在参考电压失调,子DAC输出失调或者增益错误方面获得一定的鲁棒性。     

Frequency domain identification of transfer function model of a disk drive actuator

In this paper, we present a method of identifying the transfer function model of a linear time-invariant (LTI) dynamic system from its frequency response data. The presented algorithm is based on the principle of least-square fit on the complex plane. It fits the frequency response data to the response of a transfer function model, minimizing the sum of square of residual errors. Thus a transfer function model is extracted from the measurement of the frequency response at a discrete set of frequencies. We select the order of the transfer function model through the interpretation of the cost functions obtained from least-square estimation (LSE) for different orders of the transfer function.The effectiveness of the proposed technique is verified by estimating the transfer function model of a hard disk drive actuator.     

Ensembles of radial basis function networks for spectroscopicdetection of cervical precancer

The mortality related to cervical cancer can be substantially reduced through early detection and treatment. However, current detection techniques, such as Pap smear and colposcopy, fail to achieve a concurrently high sensitivity and specificity. In vivo fluorescence spectroscopy is a technique which quickly, noninvasively and quantitatively probes the biochemical and morphological changes that occur in precancerous tissue. A multivariate statistical algorithm was used to extract clinically useful information from tissue spectra acquired from 361 cervical sites from 95 patients at 337-, 380-, and 460-nm excitation wavelengths. The multivariate statistical analysis was also employed to reduce the number of fluorescence excitation-emission wavelength pairs required to discriminate healthy tissue samples from precancerous tissue samples. The use of connectionist methods such as multilayered perceptrons, radial basis function (RBF) networks, and ensembles of such networks was investigated. RBF ensemble algorithms based on fluorescence spectra potentially provide automated and near real-time implementation of precancer detection in the hands of nonexperts. The results are more reliable, direct, and accurate than those achieved by either human experts or multivariate statistical algorithms     

An improved radial basis function based method for image warping

A new image warping method is proposed in this letter, which can warp a given image by some manual defined features. Based on the radial basis interpolation function algorithm, the proposed method can transform the original optimized problem into nonsingular linear problem by adding one-order term and affine differentiable condition. This linear system can get the steady unique solution by choosing suitable kernel function. Furthermore, the proposed method demonstrates how to set up the radial basis function in the target image so as to achieve supports to adopt the backward re-sampling technology accordingly which could gain the very slippery warping image. The experimental result shows that the proposed method can implement smooth and gradual image warping with multi-anchor points‘ accurate interpolation.     

干涉SAR提高地距方向分辨率的简明推导

用两种方法对干涉SAR提高地距方向分辨率进行证明.第一种方法首先证明空间分离的调频步进脉冲信号与通常的调频步进脉冲信号在匹配滤波满足一定条件时是等同的.接着证明干涉SAR在地距方向的信号模型与空间分离的调频步进脉冲信号模型是等同的,进而推导出干涉SAR地距方向的观测频谱展宽的公式.第二种方法从电磁波空间波数k在地距方向的投影出发,同样推导出干涉SAR地距方向观测频谱展宽的公式.计算表明干涉SAR两个通道的斜距相对测量误差对分辨率的改善有显著影响.     

Modulation transfer function for the acoustic microscope

A simple method to measure the modulation transfer function of an acoustic microscope is described. Theoretical results are compared with experimental measurements. An explanation of `shadowing? found in acoustic images is given.     

A simple derivation of minimal and near-minimal realization of 2-D transfer functions

The realizations of 2-D transfer functions presented in [1] are derived by an alternative procedure. This procedure is very simple, intuitively appealing, and allows cases more general than those in [1] to be effortlessly treated.     

Channel estimation for OFDM systems using adaptive radial basis function networks

We propose a new scheme for pilot-symbol-aided channel estimation in orthogonal frequency-division multiplexing (OFDM) systems in multipath fading channels, that does not require knowledge of the channel statistics (e.g., Doppler or power spectrum). It is based on using the radial basis function (RBF) network to model the dynamics of the fading process. Both one-dimensional and two-dimensional RBF networks are proposed to exploit the channel correlation in the time domain and in the time-frequency domain. The proposed RBF networks are essentially nonlinear interpolators of the pilot channels. Compared with the existing OFDM channel estimation methods based on linear filtering, the proposed new techniques offer both robustness to fading rate, and a better performance especially in relatively fast fading channels.     

Parametric optimization of micro-contact printing based thermal transfer of electrospun nanofibers

We report on the results of a parametric optimization of micro-contact printing based thermal transfer of electrospun nanofibers. Fiber electrospinning was performed with a solution of thermoplastic polymer and a collector having a rectangular open area. After electrospinning, a piece of elastomer polydimethylsiloxane (PDMS) was used to scratch nanofibers from the open area and to thermally transfer them to the surface of a glass substrate by micro-contact printing at a temperature slightly higher than the glass transition temperature of the polymer. With the help of optical measurements, we optimized the printing conditions including the temperature and printing duration. Then, the stability of the transferred nanofibers was studied with sonication at different power rates. As expected, the printed nanofibers showed a much enhanced adhesion stability, comparing to the as-deposited nanofibers. Furthermore, the nanofibers after thermal transfer could be used for patterning by using conventional photolithography and reactive ion etch techniques.     

使用逆滤波器方法获得扬声器的目标传输函数

提出了基于扬声器目标传输函数的扬声器声音重放特性修正方法.给出了用于修正的逆滤波器的求解方法,并在逆滤波器求解过程中引入正则化因子以避免过大的修正.最后讨论了不同滤波器系数长度对修正质量的影响.该方法基于目标传输函数,具有很好的实用意义,可适应不同的修正需求.