0480100 20240103214753.020171020235959.9 2017 RLS Algorithms adaptive identification logarithmic fixed-point and single-precision floating-point arithmetics cav_un_auth*0101120 Zpracování signálů Department of Signal Processing ZS ZS Department of Signal Processing Kadlec Jiří UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0330517 Zpracování signálů Department of Signal Processing ZS ZS Department of Signal Processing Likhonina Raissa UTIA-B CZ Ústav teorie informace a automatizace AV ČR, v. v. i. http://sp.utia.cz/index.php?ids=results&id=dsp_1_6 cav_un_auth*0351997 8A17006 GA MŠk CZ This software presents set of adaptive recursive least squares system identification algorithms based on the Bayesian extensions of real-time adaptive system identification as well as extending the existing recursive least square adaptive algorithms for estimation of time varying parameters in the applications of acoustic signal processing. The included reference adaptive algorithms are implemented in Matlab 2016b. Algorithms serve as „golden“ reference models for the embedded implementations on dedicated processors like Arm Cortex A9 and the FPGA programmable logic accelerators in devices the Xilinx Zynq. Algorithms are numerically robust. Algorithms are implemented in double precision floating point (64bit), single precision floating point (32bit) and in logarithmic arithmetic with precision 32bit and 19bit. This software also presents adaptive recursive least squares system identification algorithms taking advantage of dynamic normalization of the core of the algorithm into the guarantied range <1-, 1> for all variables. These algorithmic cores are suitable for the fixed-point implementation (14bit). JC 20000 20200 20206 2018 2 4 A hod 4ah 20231122142736.0 http://hdl.handle.net/11104/0276767 1 Department of Signal Processing UTIA-B 10200 COMPUTER SCIENCE, INFORMATION SYSTEMS S 2017 Soubory v repozitáři: kadlec-0480100.pdf 2017