Experiment Repository Creation Request for Adaptive Signal Processing Lab - IITD

[vlabsdev-iitd]

Repository Creation Request

Use this to get your experiment repository created or updated on GitHub under Virtual Labs organization.

1. Coordinating Institute: IIT Delhi and IIT Roorkee

2. Approver’s Name: IITD

3. Approved Proposal: Adaptive Signal Processing Lab.pdf

4. Hosted url:

5. Primary GitHub Handle Details:

   Name: Virtual Labs IIT Delhi

   GitHub Handle: vlabsdev-iitd

   Email id: vlabsdev.iitd@gmail.com

6. Secondary GitHub Handle Details:

   Name: Prof. Monika Aggarwal

   GitHub Handle: maggarwalcare

   Email id: Monika.Aggarwal@care.iitd.ac.in

[pavanchow]

@vlabsdev-iitd Please find the links for Adaptive Signal Processing Lab experiments and populate the repositories with sources of the experiments as detailed in Step 4 of the migration document

1. Understand various matrix operations, matrix decompositions, factorization and related operations - https://github.com/virtual-labs/exp-various-matrix-operations-iitd
2. Study the statistical properties of the output response of a system when the input is wide sense stationary - https://github.com/virtual-labs/exp-wide-sense-stationary-iitd
3. For a wide sense stationary signal evaluate the Correlogram, Blackman–Tukey, Windowed Periodogram, Bartlett, Welch, and Daniel spectral estimates - https://github.com/virtual-labs/exp-daniel-spectral-estimates-iitd
4. For a broadband, narrowband ARMA process and sum of sinusoids evaluate spectral estimates by evaluating various parameters using appropriate methods (yule walker, mini norm, least square, MuSiC etc.) and study various statistical properties of these estimates with various order process - https://github.com/virtual-labs/exp-arma-process-iitd
5. Estimate the signal from its noisy observation using a linear filter designed by minimizing the mean square error (Wiener Filter). Study the statistical properties error in these estimate for various filter lengths and different observed samples - https://github.com/virtual-labs/exp-noisy-observation-iitd
6. Estimate missing values in a signal from given measurements in noise (Prediction Problem). Employ linear MMSE predictor to estimate the missing samples in the signal based upon past and future values - https://github.com/virtual-labs/exp-linear-mmse-predictor-iitd
7. Simulation and comparative analysis of LMS and RLS algorithms using simulated as well real time bio-signals. Observe the effect of various adaptation factors like step size, forgetting factor - https://github.com/virtual-labs/exp-real-time-bio-signals-iitd
8. Study and implementation of Kalman filter - https://github.com/virtual-labs/exp-kalman-filter-iitd
9. Simulation of adaptive noise cancellation, interference canceling, channel equalization using appropriate adaptive filters for various scenario and compare the performance for various other variants of these adaptive algorithms - https://github.com/virtual-labs/exp-adaptive-algorithms-iitd
10. Audio synthesis using Differential DSP library - https://github.com/virtual-labs/exp-differential-dsp-library-iitd

[ravikiran2020]

IIT Roorkee request

Approver’s Name: Dr R S Anand Approved Proposal: Hosted url:

List of Experiments:

1. Simulation and comparative analysis of LMS and RLS algorithms using simulated as well as real time bio-signals. Observe the effect of various adaptation factors like step size, forgetting factor.

   i. Simulate an Autoregressive stochastic process. ii. Detect non-stationarity in stochastic processes with LMS and RLS

2. Study and implementation of Kalman filter. i. Correspondence between the initial conditions of the Kalman variables and prediction performance ii. With unforced dynamic model and noiseless state space model.

3. Simulation of adaptive noise cancellation, interference canceling, channel equalization using appropriate adaptive filters for various scenarios and compare the performance for various other variants of these adaptive algorithms. i. Implementation and analysis of Autoregressive Stochastic processes and Minimum Variance Distortion-less Beamformer using LMS and Monte-Carlo Runs. ii. Simulate an adaptive prediction and equalization with LMS and RLS Algorithm.

4. Audio synthesis using Differential DSP library

Primary GitHub Handle Details:

Name: Dr RS Anand GitHub Handle: @anandfee Email id: anandfee@gmail.com

Name: Dr Tharun Reddy GitHub Handle: tharuniitk Email id: tharun@iitk.ac.in

Name: Rajeev Kumar GitHub Handle: @rajeevfee Email id: rajeevkumar.rke@gmail.com

Name: Nipun Jain GitHub Handle: @jnipun1994 Email id: nipunjain1305@gmail.com

Name: Adarsh GitHub Handle: adarshvp123 Email id: adarshvp16@gmail.com

[ravikiran2020]

@virtual-labs/adapative-signal-and-micro-controller-iitr Please find the links for Adaptive Signal Processing Lab experiments and populate the repositories with sources of the experiments as detailed in Step 4 of the migration document.

1. Simulation and comparative analysis of LMS and RLS algorithms using simulated as well real time bio-signals. Observe the effect of various adaptation factors like step size, forgetting factor - https://github.com/virtual-labs/exp-real-time-bio-signals-iitr

2. Study and implementation of Kalman filter - https://github.com/virtual-labs/exp-kalman-filter-iitr

3. Simulation of adaptive noise cancellation, interference canceling, channel equalization using appropriate adaptive filters for various scenario and compare the performance for various other variants of these adaptive algorithms - https://github.com/virtual-labs/exp-adaptive-algorithms-iitr

4. Audio synthesis using Differential DSP library - https://github.com/virtual-labs/exp-differential-dsp-library-iitr

[rajeevfee]

@ravikiran2020 Kindly add the LDC in this repository Details Prof Tharun Kumar Reddy Email: tharunreddy87@gmail.com

[ravikiran2020]

@rajeevfee email invitation has been sent to Prof. Tharun Kumar Reddy. Please accept the invitation.

[ravikiran2020]

@rajeevfee please provide the github handle of Prof.Tharun Kumar reddy

[priya100raman]

@rajeevfee, please share the GitHub Handle of Prof. Tharun Kumar Reddy. Also, please note that he is the Lab Developer( SME/Proposer) for the lab and not the LDC.