Shakil

 

Comments and Ratings by Shakil		1 - 1 of 1
Updated	File	Comments	Rating
20 Jan 2009	CDMA Modem Program is About CDMA Modem Author: Farhat Masood	great job done

Files Matching Shakil's Watch List					View all 1 - 5 of 6
Updated		File	Tags	Downloads (last 30 days)	Comments	Rating
01 Jul 2010		HUFFMANCODING coding based on huffman method Author: Alireza LIAGHAT	communications, huffman method, comunications, huffmandict, huffmandictm	6	1	3.0 3.0 | 2 ratings
30 Jun 2006		CDMA Modem Program is About CDMA Modem Author: Farhat Masood	modem, cdma, wireless, wireless communicatio...	12	5	4.42857 4.4 | 7 ratings
27 Jun 2006		CDMA coding and Decoding The Programme is about CDMA coding and decoding. Author: Farhat Masood	cdma, coding, matlab, decoding, wireless, mimo	52	26	4.33333 4.3 | 28 ratings
12 Oct 2005		Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering. Author: Michael Kleder	basic kalman filter, kalman filter, discrete filter, linear, imtransform, filter analysis	657	87	4.4375 4.4 | 81 ratings
05 Oct 2005		CDMA MODEM Multiple access using CDMA for 2 users in an AWGN channel. Author: Waqas Mansoor	cdma, multiple access, wireless, spread spectrum, convert, modulate	24	8	4.42857 4.4 | 7 ratings

Comments and Ratings Matching Shakil's Watch List			1-5 of 168
Date	File	Comment by	Comments	Rating
05 Jan 2012	CDMA coding and Decoding The Programme is about CDMA coding and decoding.	Amaro	very good	5
05 Aug 2011	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering.	greg	Nicely documented. As a practicing engineer I would never use the implementation shown. This is the standard covariance form of the Kalman filter. In operation the statement s.P = s.P - K*s.H*s.P; causes significant issues. s.P needs to always be positive definite but with rounding this will tend to violate this assmption making the Kalman filter 'blow up' over time or with poorly conditioned data. The alternative is to process in the square root domain where the P matrix is expressed as a P=Psr'*Psr. Therefore the resuting matrix must always be positive definite and does not have this issue. An added advantage is the precision is doubled processing in this domain and can be similar to the input data resolution rather than 2x the number of bits to provide comparable precision. For more information see 'Linear estimation' Kailath, Sayed, Hassibi or 'adaptive filter thoery' Haykin IMHO one should always to filtering in the SR domain. There are also advantages of processing with separated real/imag data rather then complex if the underling data is complex.	Comment only
22 Jul 2011	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering.	prokash paul	nice doc	5
16 Jul 2011	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering.	lotfi	good !	Comment only
27 Jun 2011	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering.	Edgar lobachevskiy	excellent!! Thank you!!	5