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Udemy - Learn how to detect dominant cycles with spectrum analysis

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Udemy - Learn how to detect dominant cycles with spectrum analysis (Size: 729.4 MB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Introduction
  1. 1_ExampleDataset.pdf 356.7 KB
  1. Example dataset with 3-cycles.url 102.4 B
  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 102.4 B
  2 - Improving the Fast-Fourier-Transform
  3 - The Goertzel algorithm
  4 - Comparison & Impacts FFT vs. Goertzel-DFT
  10. (Zoom) Impact of 2% vs. 0.16% error rate in cycle projection window.url 102.4 B
  10. 10_Impact_ErrorRates.pdf 455.3 KB
  10. Impact FFT vs generalized Goertzel error rate in projection area (Description).html 819.2 B
  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 102.4 B
  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 716.8 B
  11. Source Code.en_US.srt 6.1 KB
  11. Source Code.mp4 52 MB
  9. 9_Results.pdf 129.7 KB
  9. Results Comparison FFT vs Goertzel cycle detection & error rates (Description).html 819.2 B
  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
  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 KB
  8. Generalized Goerzel algorithm to detect non-integer coefficients.en_US.srt 6 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 102.4 B
  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 102.4 B
  4. 4_Improving_ZeroPadding.pdf 242 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 KB
  5. Improving FFT resolution Using interpolation (b).en_US.srt 6.3 KB
  5. Improving FFT resolution Using interpolation (b).mp4 113 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
  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 102.4 B
  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 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 102.4 B

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.

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