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运用函数连接型神经网络研究 3 8种取代芳烃化合物的分子结构—毒性的定量构效关系 (QSAR) ,计算结果与MLR计算结果比较 ,前者比后者好。与实验结果的线性拟合相关系数 ,FLN所得结果为 0 9561~ 0 9996,MLR所得结果为 0 869~ 0 965。 相似文献
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基于理论线性溶剂化能关系研究两类局部麻醉药物的疏水性质 总被引:2,自引:0,他引:2
用理论线性溶剂化能关系建立了两类局部麻醉药物 (咪唑烷二酮类和苄醇类 )的结构—疏水性关系。结果表明 :分子的体积越大 ,两类化合物的亲脂性越强。另外 ,对咪唑烷二酮而言 ,分子的氢键碱度与其LogP值呈负相关 ,而苄醇类化合物的氢键酸度越大 ,对亲脂性越有利。 相似文献
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Fuzzy hypersemigroups 总被引:1,自引:0,他引:1
M. K. Sen Reza Ameri G. Chowdhury 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2008,12(9):891-900
We introduce the notions of fuzzy hypersemigroup, fuzzy hypergroup, fuzzy hyperideal, homomorphism, hyper congruence, fuzzy
homomorphism, fuzzy hypercongruence. The purpose of this note is the study of some characterization of fuzzy hypersemigroup,
fuzzy hyperideal of a fuzzy hypersemigroup and homomorphism and hypercongruence on a hypersemigroup. 相似文献
78.
A multimodel scheme is designed for a triggering tunnel-diode circuit. The scheme improves the transient behavior during the transition time period after switching from a stable system equilibrium point to another one which is known as a triggering process. Each model is obtained by a linearization of the circuit near an equilibrium point. Moreover, each of these models can be described as a combination of two other transfer functions describing the linearized plant behavior near two different equilibrium points. The scheme chooses online the model with the best tracking performance in order to generate the control law. Different reference transfer functions are proposed with the aim of generating the desired transient in the triggering process. Some simulations show the usefulness of this scheme. 相似文献
79.
Unal G Yezzi A Soatto S Slabaugh G 《IEEE transactions on pattern analysis and machine intelligence》2007,29(8):1322-1338
This paper addresses the problem of calibrating camera parameters using variational methods. One problem addressed is the severe lens distortion in low-cost cameras. For many computer vision algorithms aiming at reconstructing reliable representations of 3D scenes, the camera distortion effects will lead to inaccurate 3D reconstructions and geometrical measurements if not accounted for. A second problem is the color calibration problem caused by variations in camera responses that result in different color measurements and affects the algorithms that depend on these measurements. We also address the extrinsic camera calibration that estimates relative poses and orientations of multiple cameras in the system and the intrinsic camera calibration that estimates focal lengths and the skew parameters of the cameras. To address these calibration problems, we present multiview stereo techniques based on variational methods that utilize partial and ordinary differential equations. Our approach can also be considered as a coordinated refinement of camera calibration parameters. To reduce computational complexity of such algorithms, we utilize prior knowledge on the calibration object, making a piecewise smooth surface assumption, and evolve the pose, orientation, and scale parameters of such a 3D model object without requiring a 2D feature extraction from camera views. We derive the evolution equations for the distortion coefficients, the color calibration parameters, the extrinsic and intrinsic parameters of the cameras, and present experimental results. 相似文献
80.
Recent studies have employed simple linear dynamical systems to model trial-by-trial dynamics in various sensorimotor learning tasks. Here we explore the theoretical and practical considerations that arise when employing the general class of linear dynamical systems (LDS) as a model for sensorimotor learning. In this framework, the state of the system is a set of parameters that define the current sensorimotor transformation-the function that maps sensory inputs to motor outputs. The class of LDS models provides a first-order approximation for any Markovian (state-dependent) learning rule that specifies the changes in the sensorimotor transformation that result from sensory feedback on each movement. We show that modeling the trial-by-trial dynamics of learning provides a substantially enhanced picture of the process of adaptation compared to measurements of the steady state of adaptation derived from more traditional blocked-exposure experiments. Specifically, these models can be used to quantify sensory and performance biases, the extent to which learned changes in the sensorimotor transformation decay over time, and the portion of motor variability due to either learning or performance variability. We show that previous attempts to fit such models with linear regression have not generally yielded consistent parameter estimates. Instead, we present an expectation-maximization algorithm for fitting LDS models to experimental data and describe the difficulties inherent in estimating the parameters associated with feedback-driven learning. Finally, we demonstrate the application of these methods in a simple sensorimotor learning experiment: adaptation to shifted visual feedback during reaching. 相似文献