{"id":19815321,"url":"https://github.com/costasak/icassp2023","last_synced_at":"2026-06-08T01:02:17.093Z","repository":{"id":103743137,"uuid":"555374218","full_name":"CostasAK/icassp2023","owner":"CostasAK","description":"Jupyter Notebook associated with our submission for the 2023 ICASSP, \"Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound\"","archived":false,"fork":false,"pushed_at":"2024-01-10T20:29:18.000Z","size":1407,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-28T19:27:29.589Z","etag":null,"topics":["angle-of-arrival","array-processing","icassp","icassp2023","jupyter","jupyter-notebook","multi-target","notebook","sensor-selection","signal-processing","sparse-sensing"],"latest_commit_sha":null,"homepage":"https://icassp2023.kokke.eu/","language":"Jupyter Notebook","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/CostasAK.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-10-21T13:03:35.000Z","updated_at":"2025-02-05T09:25:40.000Z","dependencies_parsed_at":null,"dependency_job_id":"47570ef1-5907-444c-be88-97aab1c94e25","html_url":"https://github.com/CostasAK/icassp2023","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/CostasAK/icassp2023","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CostasAK%2Ficassp2023","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CostasAK%2Ficassp2023/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CostasAK%2Ficassp2023/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CostasAK%2Ficassp2023/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CostasAK","download_url":"https://codeload.github.com/CostasAK/icassp2023/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CostasAK%2Ficassp2023/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34043822,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-07T02:00:07.652Z","response_time":124,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["angle-of-arrival","array-processing","icassp","icassp2023","jupyter","jupyter-notebook","multi-target","notebook","sensor-selection","signal-processing","sparse-sensing"],"created_at":"2024-11-12T10:05:32.206Z","updated_at":"2026-06-08T01:02:17.081Z","avatar_url":"https://github.com/CostasAK.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound\n\n[\u003cimg src=\"./icassp2023-acceptance-landscape-image.png\" align=\"right\" width=\"428px\"/\u003e](https://2023.ieeeicassp.org)\nNotebook associated with our submission for the 2023 ICASSP.\n\n## Viewing\n\nThe notebook can be viewed online by opening it in nbviewer or Google Colab. The integrated notebook viewer of GitHub cannot show the plot, but it will show everything else.\n\n[![Open in nbviewer](https://img.shields.io/static/v1?label\u0026message=Open+in+nbviewer\u0026color=343433\u0026style=for-the-badge\u0026logo=jupyter)](https://nbviewer.org/github/CostasAK/icassp2023/blob/main/crb_sparse_sensing.ipynb)\n[![Open in Colab](https://img.shields.io/static/v1?label\u0026message=Open+in+Colab\u0026color=097ABB\u0026style=for-the-badge\u0026logo=googlecolab)](https://colab.research.google.com/github/CostasAK/icassp2023/blob/main/crb_sparse_sensing.ipynb)\n\n## Usage\n\nTested using Pipenv and Jupyter in Visual Studio Code on Ubuntu 20.04.\n\n1. `git clone` this repository and `cd` into the directory.\n2. (optional) `export PIPENV_VENV_IN_PROJECT=1` to install Pipenv virtual environments into the current project folder.\n3. `pipenv install`.\n4. Open this folder in Visual Studio Code.\n5. Install the workspace recommended extension.\n6. Open `crb_sparse_sensing.ipynb`.\n\nAlternatively, you can try and run a Jupyter server manually, or use Google Colab. Note that in Google Colab the errorbars on the last 2 plots might not be supported unless you update to a newer version of `scipy`.\n\n[![Open in Colab](https://img.shields.io/static/v1?label\u0026message=Open+in+Colab\u0026color=097ABB\u0026style=for-the-badge\u0026logo=googlecolab)](https://colab.research.google.com/github/CostasAK/icassp2023/blob/main/crb_sparse_sensing.ipynb)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcostasak%2Ficassp2023","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcostasak%2Ficassp2023","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcostasak%2Ficassp2023/lists"}