The Kalman filter is an efficient recursive filter that estimates the state of a linear dynamic system from a series of noisy measurements. It is used in a wide range of engineering applications from radar to computer vision, and is an important topic in control theory and control systems engineering. Together with the linear-quadratic regulator (LQR), the Kalman filter solves the linear-quadratic-Gaussian control problem (LQG). The Kalman filter, the linear-quadratic regulator and the linear-quadratic-Gaussian controller are solutions to what probably are the most fundamental problems in control theory.
Some time ago, I stated in another article that I d take the idea of location broadcasting and develop a mobile solution as a follow-up. The problem back then was I had no means to get location data off of a cell phone, or a way to make it useful. My, how times have changed since then! In this article, I ll demonstrate how to get your phone s GPS coordinates…
face detection
Face detection can be regarded as a more general case of face localization In face localization, the task is to find the locations and sizes of a known number of faces (usually one). In face detection, one does not have this additional information.
Early face-detection algorithms focused on the detection of frontal human faces, whereas newer algorithms attempt to solve the more general and difficult problem of multi-view face detection. That is, the detection of faces that are either rotated along the axis from the face to the observer (in-plane rotation), or rotated along the vertical or left-right axis (out-of-plane rotation),or both.
This file for experiment of C8051 Microcontroller(SILABS company) with USB interface that use keil programming
if you have some problem for this file, please contact me with sofa24@hotmail.com
卡耐基.梅隆大學的牛發寫的關于孤立點和數據清洗的文章，全英文，2003年完成，Probabilistic Noise Identification and Data Cleaning，Real world data is never as perfect as we would like it
to be and can often suffer from corruptions that may impact
interpretations of the data, models created from the
data, and decisions made based on the data. One approach
to this problem is to identify and remove records that contain
corruptions. Unfortunately, if only certain fields in a
record have been corrupted then usable, uncorrupted data
will be lost. In this paper we present LENS, an approach for
identifying corrupted fields and using the remaining noncorrupted
fields for subsequent modeling and analysis.
RSA ( Rivest Shamir Adleman )is crypthograph system that used to give a secret information and digital signature . Its security based on Integer Factorization Problem (IFP). RSA uses an asymetric key. RSA was created by Rivest, Shamir, and Adleman in 1977. Every user have a pair of key, public key and private key. Public key (e) . You may choose any number for e with these requirements, 1< e <Æ (n), where Æ (n)= (p-1) (q-1) ( p and q are first-rate), gcd (e,Æ (n))=1 (gcd= greatest common divisor). Private key (d). d=(1/e) mod(Æ (n)) Encyption (C) . C=Mª mod(n), a = e (public key), n=pq Descryption (D) . D=C° mod(n), o = d (private key
A sparse variant of the Levenberg-Marquardt algorithm implemented by levmar has been applied to bundle adjustment, a computer vision/photogrammetry problem that typically involves several thousand variables
