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文章/文档 For this reason, iterative soft decoding has been studied to approach the optimal ML decoding perf
For this reason,
iterative soft decoding has been studied to approach the optimal
ML decoding performance at affordable complexity.
金融证券系统 optimal portfoilio EXCELmin risk max return
optimal portfoilio EXCELmin risk max return
数学计算 计算一般形式弹性张量最优化TI近似的C程序 Computing the optimal TI approximation of a general elastic tensor
计算一般形式弹性张量最优化TI近似的C程序
Computing the optimal TI approximation of a general elastic tensor
文件格式 An optimal neuron evolution algorithm for the restoration of linearly distorted images is presented
An optimal neuron evolution algorithm for the restoration
of linearly distorted images is presented in this paper. The proposed
algorithm is motivated by the symmetric positive-definite quadratic programming
structure inherent in restoration. Theoretical analysis and experimental
results show that t ...
操作系统开发 particle swarm optimal
particle swarm optimal
其他 Optimal Subspace-Based Signal Processing
Optimal Subspace-Based Signal
Processing，美国The University of Rhode Island关于阵列信号处理中DOA的课件
书籍源码 MATLAB Code for Optimal Quincunx Filter Bank Design Yi Chen July 17, 2006 This file introduces t
MATLAB Code for Optimal Quincunx Filter
Bank Design
Yi Chen
July 17, 2006
This file introduces the MATLAB code that implements the two algorithms (i.e., Algorithms
1 and 2 in [1], or Algorithms 4.1 and 4.2 in [2]) used for the construction of
quincunx filter banks with perfect reconstruction, linear ...
系统设计方案 DESIGN OF AN OPTIMAL CONTROLLER WITH PRESCRIBED 基于最优极点配置复合控制的弹性连杆机构主动控制研究 用最优极点配置确定PID参数
DESIGN OF AN OPTIMAL CONTROLLER WITH PRESCRIBED
基于最优极点配置复合控制的弹性连杆机构主动控制研究
用最优极点配置确定PID参数
数据结构 Optimal Binary Index Assignments for a Class of Equiprobable Scalar and Vector Quantizers
Optimal Binary Index Assignments for a Class of
Equiprobable Scalar and Vector Quantizers
matlab例程 This function applies the Optimal Brain Surgeon (OBS) strategy for ％ pruning neural network models
This function applies the Optimal Brain Surgeon (OBS) strategy for
％ pruning neural network models of dynamic systems. That is networks
％ trained by NNARX, NNOE, NNARMAX1, NNARMAX2, or their recursive
％ counterparts.