搜索结果: 1-15 共查到“知识库 应用统计数学”相关记录270条 . 查询时间(3.344 秒)
基于区域卷积网络的行驶车辆检测算法
行驶车辆检测 卷积神经网络 联合训练
2022/3/28
为解决多种天气与多种场景下主干道路行驶车辆检测存在的实时性、泛化能力差、漏检、定位不准确等问题，研究了基于TensorFlow深度学习框架的区域卷积神经网络（FasterR-CNN）算法，通过引入VGG16神经网络模型，优化ROIPoolingLayer，并采用联合训练方法，得到改进的算法模型。采用UA_CAR数据集进行模型训练〖BFQ〗，实现行驶中的车辆检测，测试结果与优化前FasterR-CN...
流动聚焦型微流控装置能够方便、高效地生成均一度好且大小精确可调的微液滴(气泡)，故被广泛应用于颗粒材料合成、药物封装、细胞培养等诸多领域. 进一步优化通道结构有助于实现对合成微粒粒径、均一度和尺寸范围的精确调控. 本文数值研究了通道深度、缩颈段长度以及两相夹角等几何构型因素对流动聚焦生成微液滴直径及其生成周期各个阶段的影响. 控制液滴生成方式为滴流式，发现液滴直径随通道深度d 的增加近似呈线性增大...
Assessing Beijing's PM2:5 Pollution: Severity, Weather Impact, APEC and Winter Heating
discrepancy generalized wordtype pattern U design stochastic algorithm
2016/1/20
Orthogonal array based-Latin hypercubes, also called U designs, have popularly been adopted for designing a computer experiment. The relationship between the averaged squared discrepancy of all U desi...
Wald Lecture I: Counting Bits with Kolmogorov and Shannon
Rate-Distortion Gaussian Process Entrop Ellipsoids
2015/8/21
Shannon’s Rate-Distortion Theory describes the number of bits needed to approximately
represent typical realizations of a stochastic process X = (X(t) : t ∈ T),while Kolmogorov’s
-entropy describes...
Regularization Paths for Cox’s Proportional Hazards Model via Coordinate Descent
survival Cox model lasso elastic net
2015/8/21
We introduce a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of `1 and `2 penalties (elastic net). Our algorithm fits via cyclical coordinate descent, a...
SparseNet:Coordinate Descent with Non-Convex Penalties
Sparse Regression Regularization Surface Non-convex Optimization Coordinate Descent Degrees of Freedom Variable Selection LASSO
2015/8/21
We address the problem of sparse selection in linear models. A number of non-convex penalties have been proposed in the literature for this purpose, along with a variety of convex-relaxation algorithm...
A Quantitative Approach to Incentives: Application to Voting Rules
Voting Rules Quantitative
2015/7/15
We present a general approach to quantifying a mechanism’s susceptibility to
strategic manipulation, based on the premise that agents report their preferences
truthfully if the potential gain from b...
EXPLORING THE EFFECTS OF SOCIAL PREFERENCE,ECONOMIC DISPARITY,AND HETEROGENEOUS ENVIRONMENTS ON SEGREGATION
subject classifications
2015/7/14
It is believed that social preference, economic disparity, and heterogeneous environments are mechanisms for segregation. However, it is difficult to unravel the exact role of each mechanism in such a...
Solution of the Inverse Problem of Linear Optimal Control with Positiveness Conditions and Relation to Sensitivity
Linear Optimal Control Positiveness Conditions
2015/6/23
The property that the feedback control minimizes some performance index (1.3)
with Q ≥ 0 is of considerable interest because of its connection with the ability
of the control to reduce the sensitivi...
Semidefinite Programming Relaxations and Algebraic Optimization in Control
Control Algebraic Optimization
2015/6/19
We present an overview of the essential elements of semidefinite programming as a computational tool for the analysis of systems and control problems. We make particular emphasis on general duality pr...
Empirical Model Reduction of Controlled Nonlinear Systems
Controlled Nonlinear Systems Model Reduction
2015/6/19
In this paper we introduce a new method of model reduction for nonlinear systems with inputs and outputs. The method requires only standard matrix computations, and when applied to linear systems resu...
Tractable fitting with convex polynomials via sum-of-squares
via sum-of-squares Tractable fitting
2015/6/19
We consider the problem of fitting given data with a convex polynomial. A technique to solve this problem using sum of squares polynomials is presented. This technique is extended to enforce convexity...
Decentralized Stochastic Decision Problems and Polynomial Optimization
Decision Problems Polynomial Optimization
2015/6/19
In this paper we consider the problem of computing decentralized control policies in a discrete stochastic decision problem. For the problem we consider, computation of optimal decentralized policies ...
A Constant Factor Approximation Algorithm for Event-Based Sampling
Event-Based Sampling Approximation Algorithm
2015/6/19
We consider a control system in which sensor data is transmitted from the plant to a receiver over a communication channel, and the receiver uses the data to estimate the state of the plant. Using a f...