Download Udemy - Learn how to detect dominant cycles with spectrum analysis torrent

Udemy - Learn how to detect dominant cycles with spectrum analysis

Torrent:	Udemy - Learn how to detect dominant cycles with spectrum analysis
Description:	Learn how to detect dominant cycles with spectrum analysis https://WebToolTip.com Last updated 11/2023 MP4 \| Video: h264, 1920x1080 \| Audio: AAC, 44.1 KHz, 2 Ch Language: English \| Duration: 49m \| Size: 729.4 MB Using the Fast Fourier Transform and the DFT-Goertzel algorithm to detect cycles in noisy data sets (financial markets) What you'll learn This course explains the key elements of a Fourier-based spectrum analysis. Understanding the basic computations involved in FFT-based or Goertzel-algorithm-based measurement. Explaining the core background of FFT in layman terms and concentrate on the important aspects on “how to read a spectrum” plot. Learn why the Goertzel algorithm outperforms classical Fourier transforms for the purpose of cycles detection in financial markets Get the source code to implement the generalized Goertzel transform Requirements Basic cycle and/or spectrum analysis knowledge is helpfull, but not mandatory.
Downloads:	37
Category:	Other /Tutorials
Size:	729.4 MB
Show Files »	[ WebToolTip.com ] Udemy - Learn how to detect dominant cycles with spectrum analysis Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here ! 1 - Introduction 1. 1_ExampleDataset.pdf (356.7 KB) 1. Example dataset with 3-cycles.url (0.1 KB) 1. Introduction - Example dataset with 3 cycles (Description).html (1.1 KB) 1. Introduction - Example dataset with 3 cycles.en_US.srt (1.7 KB) 1. Introduction - Example dataset with 3 cycles.mp4 (24.6 MB) 1. Raw test signal (N=800).url (0.1 KB) 2. 2_Applying_FFT.pdf (252.4 KB) 2. Applying the Fast Fourier Transform “FFT” for cycle detection (Description).html (1.2 KB) 2. Applying the Fast Fourier Transform “FFT” for cycle detection.en_US.srt (12.3 KB) 2. Applying the Fast Fourier Transform “FFT” for cycle detection.mp4 (185.8 MB) 2. FFT Spectrum.url (0.1 KB) 3. 3_Fourier_Indexpdf.pdf (222.4 KB) 3. The Fourier index coefficient – time frequency conversion (Description).html (1.5 KB) 3. The Fourier index coefficient – time frequency conversion.en_US.srt (1.0 KB) 3. The Fourier index coefficient – time frequency conversion.mp4 (9.7 MB) 3. k-th Frequency Coefficient vs Cycle Length (for dataset N=800).url (0.1 KB) 2 - Improving the Fast-Fourier-Transform 4. 4_Improving_ZeroPadding.pdf (242.0 KB) 4. Improving FFT resolution using zero padding (a) (Description).html (1.1 KB) 4. Improving FFT resolution using zero padding (a).en_US.srt (4.6 KB) 4. Improving FFT resolution using zero padding (a).mp4 (58.3 MB) 5. 5_Improving_Interpolaton.pdf (183.4 KB) 5. Improving FFT resolution Using interpolation (b) (Description).html (1.0 KB) 5. Improving FFT resolution Using interpolation (b).en_US.srt (6.3 KB) 5. Improving FFT resolution Using interpolation (b).mp4 (113.0 MB) 6. 6_Improving_WeightedAverage.pdf (676.2 KB) 6. Improving FFT resolution Weighted average around cycle peaks (c) (Description).html (1.1 KB) 6. Improving FFT resolution Weighted average around cycle peaks (c).en_US.srt (1.5 KB) 6. Improving FFT resolution Weighted average around cycle peaks (c).mp4 (19.9 MB) 3 - The Goertzel algorithm 7. 7_Goertzel.pdf (202.8 KB) 7. The Goertzel algorithm to detect cycles (Description).html (1.6 KB) 7. The Goertzel algorithm to detect cycles.en_US.srt (3.6 KB) 7. The Goertzel algorithm to detect cycles.mp4 (73.6 MB) 8. 8_Generalized_Goertzel.pdf (410.4 KB) 8. Generalized Goerzel algorithm to detect non-integer coefficients (Description).html (2.0 KB) 8. Generalized Goerzel algorithm to detect non-integer coefficients.en_US.srt (6.0 KB) 8. Generalized Goerzel algorithm to detect non-integer coefficients.mp4 (110.6 MB) 8. Goertzel algorithm generalized to non-integral multiples of fundamental frequency (MATLAB).url (0.1 KB) 8. Goertzel_Article_Algorithm.pdf (459.8 KB) 8. Sysel, P., Rajmic, P. Goertzel algorithm generalized to non-integer multiples of fundamental frequency. EURASIP J. Adv. Signal Process. 2012, 56 (2012).url (0.1 KB) 4 - Comparison & Impacts FFT vs. Goertzel-DFT 10. (Zoom) Impact of 2% vs. 0.16% error rate in cycle projection window.url (0.1 KB) 10. 10_Impact_ErrorRates.pdf (455.3 KB) 10. Impact FFT vs generalized Goertzel error rate in projection area (Description).html (0.8 KB) 10. Impact FFT vs generalized Goertzel error rate in projection area.en_US.srt (3.3 KB) 10. Impact FFT vs generalized Goertzel error rate in projection area.mp4 (51.9 MB) 10. Impact of 2% vs. 0.16% error rate in cycle projection window.url (0.1 KB) 9. 9_Results.pdf (129.7 KB) 9. Results Comparison FFT vs Goertzel cycle detection & error rates (Description).html (0.8 KB) 9. Results Comparison FFT vs Goertzel cycle detection & error rates.en_US.srt (2.6 KB) 9. Results Comparison FFT vs Goertzel cycle detection & error rates.mp4 (26.3 MB) 5 - Source Code - generalized Goertzel Transform 11. Gen_Goertzel.pdf (111.4 KB) 11. Generalized_Goertzel_Transform.txt (2.9 KB) 11. Source Code (Description).html (0.7 KB) 11. Source Code.en_US.srt (6.1 KB) 11. Source Code.mp4 (52.0 MB) Bonus Resources.txt (0.1 KB) files
Added:	2026-04-18 15:42:41
Language:	English
Peers:	Seeders : 7 , Leechers : 7
Tags:	Business Udemy
Release name:	Udemy - Learn how to detect dominant cycles with spectrum analysis
Trackers:	udp://tracker.torrent.eu.org:451/announce udp://tracker.tiny-vps.com:6969/announce http://tracker.foreverpirates.co:80/announce udp://tracker.cyberia.is:6969/announce udp://exodus.desync.com:6969/announce udp://explodie.org:6969/announce udp://tracker.opentrackr.org:1337/announce udp://9.rarbg.to:2780/announce udp://tracker.internetwarriors.net:1337/announce udp://ipv4.tracker.harry.lu:80/announce udp://open.stealth.si:80/announce udp://9.rarbg.to:2900/announce udp://9.rarbg.me:2720/announce udp://opentor.org:2710/announce