diff --git a/exercises/week02/Linear transforms.ipynb b/exercises/week02/Linear transforms.ipynb index 9e1a8e9e3b1393c0d0bb27024c1cffb958482375..2044e8bcb43405eddeb78a1bfc849b1b73e020f3 100644 --- a/exercises/week02/Linear transforms.ipynb +++ b/exercises/week02/Linear transforms.ipynb @@ -3,7 +3,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e039b976", + "id": "60552e92", "metadata": { "deletable": false, "editable": false @@ -28,9 +28,6 @@ "\n", "The first week notebook (introduction to Python, Numpy and Matplotlib) can be used as a help.\n", "\n", - "## Important\n", - "You need to submit *individually* your answers on moodle before the next exercise session. For the theoretical questions you can either fill the notebook or write it on a separate sheet (if you are not comfortable with Markdown/TeX) and upload a scanned version. \n", - "\n", "## Objective\n", "\n", "The end goal is to understand purely algebraic, matrix based, view of a few linear transforms. You will use those linear transform to perform some basic time-frequency analysis of signals." @@ -70,7 +67,7 @@ }, { "cell_type": "markdown", - "id": "c6cd60d1", + "id": "b6087a12", "metadata": { "tags": [ "otter_answer_cell" @@ -97,7 +94,7 @@ }, { "cell_type": "markdown", - "id": "aed5c02d", + "id": "3f0ff7a0", "metadata": { "tags": [ "otter_answer_cell" @@ -126,7 +123,7 @@ }, { "cell_type": "markdown", - "id": "db9f3b40", + "id": "d8031ee7", "metadata": { "tags": [ "otter_answer_cell" @@ -167,7 +164,7 @@ { "cell_type": "code", "execution_count": null, - "id": "a6772e5f", + "id": "2283adf4", "metadata": { "deletable": false, "editable": false @@ -248,7 +245,7 @@ }, { "cell_type": "markdown", - "id": "8389b07e", + "id": "cbde7de1", "metadata": { "tags": [ "otter_answer_cell" @@ -368,7 +365,7 @@ { "cell_type": "code", "execution_count": null, - "id": "eae601f6", + "id": "58978e43", "metadata": { "deletable": false, "editable": false @@ -397,7 +394,7 @@ }, { "cell_type": "markdown", - "id": "655fc363", + "id": "6239185e", "metadata": { "tags": [ "otter_answer_cell" @@ -469,7 +466,7 @@ }, { "cell_type": "markdown", - "id": "1ad05860", + "id": "ff1a761a", "metadata": { "tags": [ "otter_answer_cell" @@ -519,7 +516,7 @@ }, { "cell_type": "markdown", - "id": "7a80f125", + "id": "56fd9eda", "metadata": { "tags": [ "otter_answer_cell" @@ -560,7 +557,7 @@ { "cell_type": "code", "execution_count": null, - "id": "7fdfd203", + "id": "86b9b019", "metadata": { "deletable": false, "editable": false @@ -614,7 +611,7 @@ { "cell_type": "code", "execution_count": null, - "id": "e6d9e517", + "id": "c3138843", "metadata": { "deletable": false, "editable": false @@ -639,7 +636,7 @@ }, { "cell_type": "markdown", - "id": "ee4201b9", + "id": "02e21ab7", "metadata": { "tags": [ "otter_answer_cell" @@ -885,7 +882,7 @@ { "cell_type": "code", "execution_count": null, - "id": "4ab6578e", + "id": "d5cb5707", "metadata": { "deletable": false, "editable": false @@ -912,7 +909,7 @@ }, { "cell_type": "markdown", - "id": "9a63dd83", + "id": "a999fadd", "metadata": { "tags": [ "otter_answer_cell" @@ -924,7 +921,7 @@ }, { "cell_type": "markdown", - "id": "43d32956", + "id": "e705a9ec", "metadata": { "deletable": false, "editable": false