The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application.
標簽： filtering particle Blackwellised conditionall
上傳時間： 2013-12-17
上傳用戶：zsjzc
一些數據庫的實例。共12章。如第八章： 第8章數據庫環境的建立 1. 用MISDBA用戶登錄MISDB數據庫。 2. 在ISQL中，輸入第8章提供的SQL語句；或者根據表8-1至表8-4在SQL Explorer中自行創建數據表。 3. 根據表8-5至表8-7設置初始數據，另外需要在PERSON數據表中設置一個具有培訓管理系統管理權限的用戶（ID=’PXC’，PASSWD=’PASSWORD’，AUTHORITY=’6’，STATE=’F’）和用于外派培訓的用戶（ID=’PXCOUT’，NAME=’外派培訓’）。 4. 修改Admin源程序中的數據庫連接屬性，并且重新編譯training.exe。 5. 修改Client源程序中數據庫連接屬性，并且重新生成html文件和cab文件，然后將這兩個文件拷貝到web服務器指定目錄中。
上傳時間： 2014-01-09
上傳用戶：zxc23456789
1. 用SYSDBA登錄服務器，并且創建一個MISDBA用戶，密碼為PASSWORD。 2. 用SYSDBA用戶創建MISDB數據庫（可直接注冊使用光盤提供的MISDB.GDB）。 3. 用MISDBA用戶登錄MISDB數據庫。 4. 在ISQL中，依次輸入第5章的數據表創建SQL語句；或者根據表5-1至表5-7自行創建數據表。 5. 在SQL Explorer中創建MISDB數據庫連接。 6. 用MISDBA用戶登錄，并且輸入原始數據。除了表5-8至表5-11的內容，還需要根據需要設置部門（DEPARTMENT）、職務（JOB）和人事科登錄用戶（ID=’RSK’，PASSWD=’RSK’，AUTHORITY=’3’，STATE=’F’）。 7. 修改源程序中的數據庫連接組件參數。
上傳時間： 2013-12-16
上傳用戶：縹緲
1. 在IBConsole中添加兩個用戶LOGIN和MATER，密碼均為PASSWORD。 2. 用MISDBA用戶登錄MISDB數據庫。 3. 在ISQL中，輸入第9章提供的SQL語句；或者根據表9-1至表9-8在SQL Explorer中自行創建數據表。數據庫創建后需要分配LOGIN和MATER用戶的訪問權限。 4. 根據表9-9和表9-10設置初始數據，另外需要在PERSON數據表中設置一個用于登錄系統的用戶（ID=’MAT’，PASSWD=’PASSWORD’，AUTHORITY=’7’，STATE=’F’），同時在PART表中添加ID為’0000000000’的零件，名稱為“。 5. 除了修改數據庫連接的屬性，還需要修改數據模塊中LOGIN方法的相關用戶密碼。
上傳時間： 2014-08-06
上傳用戶：xiaohuanhuan
這是一個非常簡單的遺傳算法源代碼，是由Denis Cormier (North Carolina State University)開發的，Sita S.Raghavan (University of North Carolina at Charlotte)修正。
上傳時間： 2014-12-05
上傳用戶：aa17807091
This section contains a brief introduction to the C language. It is intended as a tutorial on the language, and aims at getting a reader new to C started as quickly as possible. It is certainly not intended as a substitute for any of the numerous textbooks on C. 2. write a recursive function FIB (n) to find out the nth element in theFibanocci sequence number which is 1,1,2,3,5,8,13,21,34,55,…3. write the prefix and postfix form of the following infix expressiona + b – c / d + e * f – g * h / i ^ j4. write a function to count the number of nodes in a binary tr
標簽： introduction the contains intended
上傳時間： 2013-12-23
上傳用戶：liansi
ReBEL is a Matlabtoolkit of functions and scripts, designed to facilitate sequential Bayesian inference (estimation) in general state space models. This software consolidates research on new methods for recursive Bayesian estimation and Kalman filtering by Rudolph van der Merwe and Eric A. Wan. The code is developed and maintained by Rudolph van der Merwe at the OGI School of Science & Engineering at OHSU (Oregon Health & Science University).
標簽： Matlabtoolkit facilitate sequential functions
上傳時間： 2015-08-31
上傳用戶：皇族傳媒
* This a software code module for a time-of-day clock object. * The clock may be fixed 12-hour, fixed 24-hour, or dynamically * configurable between these two types. Clock data can be accessed * as a binary number representing the number of minutes since midnight * or a BCD number formatted according to the time-of-day description * in the TIME module 0404x. The functions work with time-of-day values * which conform to normally accepted clock values of 1:00 to * 12:59 BCD / 0 to 719 binary for a 12-hour clock or clock values * 00:00 to 23:59 BCD / 0 to 1439 binary for a 24-hour clock. On power-up * the clock is 12:00 BCD / 0 binary for a 12-hour or dynamically * configurable clock, or 00:00 BCD / 0 binary for a 24-hour clock.
標簽： clock time-of-day software module
上傳時間： 2013-12-07
上傳用戶：llandlu
Knowledge of the process noise covariance matrix is essential for the application of Kalman filtering. However, it is usually a difficult task to obtain an explicit expression of for large time varying systems. This paper looks at an adaptive Kalman filter method for dynamic harmonic state estimation and harmonic injection tracking.
標簽： application covariance Knowledge essential
上傳時間： 2014-01-19
上傳用戶：litianchu
This paper deals with the problem of speech enhancement when a corrupted speech signal with an additive colored noise is the only information available for processing. Kalman filtering is known as an effective speech enhancement technique, in which speech signal is usually modeled as autoregressive (AR) process and represented in the state-space domain.
標簽： speech with enhancement corrupted
上傳時間： 2015-09-07
上傳用戶：zhangyi99104144
