文件列表:

armasa (0, 2008-01-23)
armasa\ASA (0, 2008-01-23)
armasa\ASAaddpath.m (1762, 2001-04-03)
armasa\ASArmpath.m (163, 2000-11-16)
armasa\ASA\ASAarg.m (5049, 2001-02-05)
armasa\ASA\ASAcontrol (0, 2008-01-23)
armasa\ASA\ASAcontrol\Contents.m (6294, 2001-04-03)
armasa\ASA\ASAerr.m (1978, 2001-02-05)
armasa\ASA\ASAglob.m (2988, 2001-02-05)
armasa\ASA\ASAglobretr.m (942, 2001-02-05)
armasa\ASA\ASAglob_ar_cond (0, 2008-01-23)
armasa\ASA\ASAglob_ar_cond\Contents.m (1126, 2001-04-03)
armasa\ASA\ASAglob_mean_adj (0, 2008-01-23)
armasa\ASA\ASAglob_mean_adj\Contents.m (1215, 2001-04-03)
armasa\ASA\ASAglob_subtr_mean (0, 2008-01-23)
armasa\ASA\ASAglob_subtr_mean\Contents.m (1086, 2001-04-03)
armasa\ASA\ASAversion2numstr.m (1815, 2001-02-05)
armasa\ASA\ASAversionbkup.m (1442, 2001-02-05)
armasa\ASA\ASAversionchk.m (3716, 2001-03-21)
armasa\ASA\ASAwarn.m (2606, 2001-02-05)
armasa\ASA\check (0, 2008-01-23)
armasa\ASA\check\contents.m (94, 2001-02-05)
armasa\ASA\check\isascending.m (325, 2000-11-02)
armasa\ASA\check\isintscalar.m (161, 2001-02-07)
armasa\ASA\check\isintvector.m (219, 2001-02-07)
armasa\ASA\check\isnum.m (203, 2000-11-04)
armasa\ASA\check\isscalar.m (104, 2000-12-22)
armasa\ASA\check\isvector.m (97, 2000-11-04)
armasa\ASA\contents.m (94, 2001-02-05)
armasa\ASA\help (0, 2008-01-23)
armasa\ASA\help\ar2arset.doc (31744, 2001-02-04)
armasa\ASA\help\arma2cor.doc (41984, 2001-02-05)
armasa\ASA\help\arma2psd.doc (39424, 2001-02-05)
armasa\ASA\help\armafilter.doc (35840, 2001-02-05)
armasa\ASA\help\armasel.doc (23552, 2001-02-05)
armasa\ASA\help\ASAarg.doc (53248, 2001-02-05)
armasa\ASA\help\ASAcontrol.doc (31232, 2001-02-08)
armasa\ASA\help\ASAerr.doc (38400, 2001-01-10)
armasa\ASA\help\ASAglob.doc (55296, 2001-02-01)
armasa\ASA\help\ASAglobretr.doc (28672, 2001-01-30)
... ...

http://www.dcsc.tudelft.nl/Research/Software/index.html ARMASA Toolbox for use with Matlab ================================== This ARMASA Toolbox is developed on a Windows OS platform using Matlab R11.1 and tested, optimizing performance, using Matlab R12. Care has been taken to develop program code that should also run well on platforms with other operating systems. Required Matlab version (any OS): R11 Title to ownership ------------------ Any part of the ARMASA software package may freely be used for scientific or educational purposes. For commercial applications, permission is required from P.M.T. Broersen (address stated below). How to Install -------------- 1. Unzip the file ARMASA_X_X.ZIP (X = number) to a directory where you want the main ARMASA directory to reside. An obvious choice is to locate it where other Matlab toolboxes are installed. To do this choose '...\Matlab\Toolbox' as the directory to extract the files. Be sure the 'Use folder names option' is checked. 2. Start Matlab. 3. Select the ARMASA directory as the current working directory in Matlab. From the command prompt, using the command 'cd' and typing the full path to the ARMASA directory, will do so. Type 'help cd' for more information. Alternatively, you can use the graphical user interface, like the path browser in R11. 4. Type 'ASAaddpath'. Search paths, needed to access the various functions of the ARMASA toolbox, will then be added to the default search paths. You must decide whether the paths will be "prepended" to the existing paths, resulting in the highest priority compared to other functions on search, or "appended", resulting in the lowest search priority. How to Uninstall ---------------- 1. Start Matlab. 2. Type 'ASArmpath' to remove the previously added ARMASA toolbox paths. 3. Remove the directory ARMASA and its entire contents. To Get Started with ARMASA -------------------------- Once installed, type 'help ARMASA'. User support ------------ References: P. M. T. Broersen, Automatic Spectral Analysis with Time Series Models, IEEE Transactions on Instrumentation and Measurement, Vol. 51, No. 2, April 2002, pp. 211-216. P. M. T. Broersen, Autoregressive Model Orders for Durbin's MA and ARMA estimators, IEEE Transactions on Signal Processing, Vol. 48, No. 8, August 2000, pp. 2454-2457. P. M. T. Broersen, Finite Sample Criteria for Autoregressive Order Selection. IEEE Trans. on Signal Processing, vol. 48, no. 12, pp. 3550-3558, 2000. Any questions on the theoretical foundations and the applicability of the functions can be submitted to: broersen@tn.tudelft.nl P.M.T. Broersen Delft University of Technology Faculty of Applied Sciences Department of Applied Physics Signals, Systems and Control Group Lorentzweg 1 2628 CJ Delft the Netherlands telephone: +31 15 278***19 Any questions about program specific details and bug reports can be submitted to the programmer: wwunderink01@freeler.nl Wouter Wunderink telephone (private): +31 10 4190343

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