Search and discovery in an uncertain networked world

This paper identifies two classes of sensor network problems that arise naturally in many applications. Fusion problem involves correlated data over the sensor network, while search/sensor selection involves selecting sensors that have useful information. The paper also describes an adaptive decision making system, which feeds back the previous decisions of the sensor network to make more informed decisions in the succeeding steps of the algorithm. The ideas that are developed for fusion problems proved to be useful in successfully executing the described algorithm. Problems such as target tracking in clutter and sensor selection can be fitted into the framework of this class.     

应用判决反馈的混合信号单通道盲分离算法

该文提出了一种基于判决反馈思想的DF-PSP单通道盲分离算法。该算法结合判决反馈的思想,利用Viterbi序列检测器最可能的幸存序列得到的预判决来合成信道冲激响应尾部造成的符号串扰,来弥补现有PSP单通道盲分离算法对信道冲激响应进行截断处理而带来的性能损失。仿真结果表明,对于两路混合QPSK信号,该算法较截断PSP单通道盲分离算法在复杂度相当的条件下有更好的性能,在误码率为 时,信噪比改善可达到2dB左右,且在同等过采样条件下,该算法能获得更好的性能提升。      

Dynamic image data compression in spatial and temporal domains:theory and algorithm

Advanced medical imaging requires storage of large quantities of digitized clinical data. These data must be stored in such a way that their retrieval does not impair the clinician's ability to make a diagnosis. We propose a theory and algorithm for near lossless dynamic image data compression. Taking advantage of domain-specific knowledge related to medical imaging, medical practice and the dynamic imaging modality, a compression ratio greater than 80:1 is achieved. The high compression ratios are achieved by the proposed algorithm through three stages: (1) addressing temporal redundancies in the data through application of image optimal sampling, (2) addressing spatial redundancies in the data through cluster analysis, and (3) efficient coding of image data using standard still-image compression techniques. To illustrate the practicality of the algorithm, a simulated positron emission tomography (PET) study using the fluoro-deoxy-glucose (FDG) tracer is presented. Realistic dynamic image data are generated by virtual scanning of a simulated brain phantom as a real PET scanner. These data are processed using the conventional and proposed algorithms as well as the techniques for storage and analysis. The resulting parametric images obtained from the conventional and proposed approaches are subsequently compared to evaluate the proposed compression algorithm. The storage space for dynamic image data reduced by more than 95%, without loss in diagnostic quality. Therefore, the proposed theory and algorithm are expected to be very useful in medical image database management and telecommunication     

Initial and boundary conditions in multidimensional wave digital filter algorithms for plate vibration

Recently, multidimensional wave digital filter (MDWDF) structures have been proposed for the modeling of plate vibration problems. In this paper, we discuss how initial and boundary conditions may be properly embedded into such an algorithm in terms of the state quantities that are an integral part of the algorithm. Due to the essential feature of fully-local interconnectivity in the MDWDF model, different types of boundary conditions can be easily satisfied in a very simple and efficient manner. Instead of remodifying the whole algorithm, usually required by finite elements based methods, boundary conditions in terms of state outputs are simply attached to the model. This feature is especially useful when dealing with the mixed-edges boundary conditions frequently encountered in practice. Graphical results obtained from implementing the MDWDF algorithm are given to further demonstrate the capacities of the method in efficiently handling a fourth-order Mindlin plate vibration system with various types of boundary conditions.     

Realization of modular multidimensional complex digital filters using GIC concept

It is known that complex digital filters possess certain advantages over real digital filters in processing complex signals such as increased computational speed and efficiency. In this paper, a simple and systematic procedure which can be implemented through a computer program is presented for realizing a specific class of multidimensional (M-D) complex digital filters. The proposed filter structures are derived from analog reference configurations comprising generalized immittance converters and resistors by making use of wave concept. These filters possess many salient properties such as low noise, low sensitivity and capability of realizing multiple transfer functions simultaneously which are inherited from the reference analog filters they are derived from. These features make them attractive for very large-scale integrated (VLSI) implementation. It is shown that the proposed filter structures can be obtained directly from the specified M-D discrete transfer function without the need for realizing any analog reference configuration.     

地基MIMO雷达快速成像算法研究

地基多输入多输出(Multiple-Input Multiple-Output, MIMO)成像雷达采用数字波束形成技术实现二维成像,具有成像速度快的技术优势。本文提出了一种适用于大景深、宽视角场景的地基MIMO雷达的快速二维成像算法。首先,根据MIMO雷达的阵列构型建立回波信号模型;其次,基于该模型补偿天线阵列近场空变性的相位中心近似(Phase Center Approximation, PCA)误差并进行数据重排,通过Kesytone变换校正距离徙动;然后,利用方位分块Dechirp处理实现方位向聚焦,实现MIMO雷达二维成像;最后利用MIMO雷达外场实验数据完成了算法验证。研究结果表明:在保证成像精度要求的情况下,该算法可以实现大景深、宽视角场景的高分辨快速成像,成像处理时间优于反向投影成像(Back Projection, BP)算法。      

Confident interpretation of Bayesian decision tree ensembles for clinical applications.

Bayesian averaging (BA) over ensembles of decision models allows evaluation of the uncertainty of decisions that is of crucial importance for safety-critical applications such as medical diagnostics. The interpretability of the ensemble can also give useful information for experts responsible for making reliable decisions. For this reason, decision trees (DTs) are attractive decision models for experts. However, BA over such models makes an ensemble of DTs uninterpretable. In this paper, we present a new approach to probabilistic interpretation of Bayesian DT ensembles. This approach is based on the quantitative evaluation of uncertainty of the DTs, and allows experts to find a DT that provides a high predictive accuracy and confident outcomes. To make the BA over DTs feasible in our experiments, we use a Markov Chain Monte Carlo technique with a reversible jump extension. The results obtained from clinical data show that in terms of predictive accuracy, the proposed method outperforms the maximum a posteriori (MAP) method that has been suggested for interpretation of DT ensembles.     

医学图像模糊增强方法研究

针对传统医学图像增强效果不理想、边界模糊不清、不利于病情诊断等问题,提出了一种改进的医学图像增强算法。首先创建一个适合的隶属度函数实现图像由时域到变换域的变换,通过迭代方法加强变换域的细节成分,最后通过模糊逆变换得到增强后的时域图像。采用的适合隶属度函数,增强了图像效果,使图像细节更清晰。实验表明,采用模糊方法比传统的几种方法可以更有效抑制噪声,提取医学图像中的有用信息,更加有利于病情的诊断。     

一种简化的LDPC码BP译码算法的研究

低密度奇偶校验码(LDPC码)是一种逼近香农限的线性分组码,译码的复杂度较低;在LDPC码译码算法中性能较好的是置信传播译码(BP)算法,他能够在迭代译码过程中确定码字是否已译出,但是复杂度高,运算量大。采用一种改进的BP译码算法,在迭代译码过程中对校验节点的更新信息进行曲线拟合,以减小译码运算量,有利于硬件的并行实现,减少译码延时。仿真结果表明,改进的BP算法译码性能和原来的BP算法接近,而且复杂度较低。     

Morphological Clustering and Analysis of Continuous Intracranial Pressure

The continuous measurement of intracranial pressure (ICP) is an important and established clinical tool that is used in the management of many neurosurgical disorders such as traumatic brain injury. Only mean ICP information is used currently in the prevailing clinical practice, ignoring the useful information in ICP pulse waveform that can be continuously acquired and is potentially useful for forecasting intracranial and cerebrovascular pathophysiological changes. The present study introduces and validates an algorithm of performing automated analysis of continuous ICP pulse waveform. This algorithm is capable of enhancing ICP signal quality, recognizing non artifactual ICP pulses, and optimally designating the three well-established subcomponents in an ICP pulse. Validation of the proposed algorithm is done by comparing non artifactual pulse recognition and peak designation results from a human observer with those from automated analysis based on a large signal database built from 700 h of recordings from 66 neurosurgical patients. An accuracy of 97.84% is achieved in recognizing non artifactual ICP pulses. An accuracy of 90.17%, 87.56%, and 86.53% was obtained for designating each of the three established ICP subpeaks. These results show that the proposed algorithm can be reliably applied to process continuous ICP recordings from real clinical environment to extract useful morphological features of ICP pulses.