diff --git a/02-FFT_and_Basic_Filtering/1-fourier_transform.ipynb b/02-FFT_and_Basic_Filtering/1-fourier_transform.ipynb
index 8183d40..833e874 100644
--- a/02-FFT_and_Basic_Filtering/1-fourier_transform.ipynb
+++ b/02-FFT_and_Basic_Filtering/1-fourier_transform.ipynb
@@ -238,7 +238,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "scrolled": false,
     "slideshow": {
      "slide_type": "fragment"
     }
@@ -429,15 +428,26 @@
     "# reconstruct signal\n",
     "g = np.ones_like(t_) * a0\n",
     "for k, (ak, bk) in enumerate(zip(a, b)):\n",
-    "    g += ak * np.sin(bk*t_)\n",
-    "\n",
-    "# plotting\n",
+    "    g += ak * np.sin(bk*t_)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Cell 7b: plotting\n",
     "plt.plot(t_, square, 'r', label='original signal')                  \n",
     "plt.plot(t_, g, 'g', label='Reihenentwicklung')\n",
     "plt.ticklabel_format(axis='y', style='sci', scilimits=(-1,1))\n",
     "plt.xlabel('time [sec]')\n",
     "plt.ylabel('amplitude')\n",
-    "#plt.ylim(-1.1,1.1)\n",
+    "#plt.ylim(0.9,1.1)\n",
     "plt.legend()\n",
     "plt.show()"
    ]
@@ -494,14 +504,14 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "scrolled": true,
+    "scrolled": false,
     "slideshow": {
      "slide_type": "subslide"
     }
    },
    "outputs": [],
    "source": [
-    "#plotting\n",
+    "#Cell 8b: plotting\n",
     "plt.subplot(311)\n",
     "plt.title('Time Domain')\n",
     "plt.plot(t, square, linewidth=1)\n",
diff --git a/02-FFT_and_Basic_Filtering/2-filter_basics.ipynb b/02-FFT_and_Basic_Filtering/2-filter_basics.ipynb
index 1850435..79b7a74 100644
--- a/02-FFT_and_Basic_Filtering/2-filter_basics.ipynb
+++ b/02-FFT_and_Basic_Filtering/2-filter_basics.ipynb
@@ -12,7 +12,7 @@
     "    <div style=\"float: right ; margin: 50px ; padding: 20px ; background: rgba(255 , 255 , 255 , 0.7) ; width: 50% ; height: 150px\">\n",
     "        <div style=\"position: relative ; top: 50% ; transform: translatey(-50%)\">\n",
     "            <div style=\"font-size: xx-large ; font-weight: 900 ; color: rgba(0 , 0 , 0 , 0.8) ; line-height: 100%\">Signal Processing</div>\n",
-    "            <div style=\"font-size: large ; padding-top: 20px ; color: rgba(0 , 0 , 0 , 0.5)\">Filtering Basics</div>\n",
+    "            <div style=\"font-size: large ; padding-top: 20px ; color: rgba(0 , 0 , 0 , 0.5)\">Filtering Basics - Solution</div>\n",
     "        </div>\n",
     "    </div>\n",
     "</div>\n",
@@ -157,6 +157,7 @@
    },
    "outputs": [],
    "source": [
+    "# Cell 1b: print stats\n",
     "print(st[0].stats)"
    ]
   },
@@ -206,7 +207,7 @@
    },
    "outputs": [],
    "source": [
-    "# filtered traces\n",
+    "# Cell 2b: filtered traces\n",
     "stHP = st.copy()\n",
     "stHP.filter('highpass', freq=f0, corners=corners, zerophase=True)\n",
     "stLP = st.copy()\n",
@@ -229,13 +230,15 @@
    "execution_count": null,
    "metadata": {
     "slideshow": {
+     "rise": {
+      "scroll": true
+     },
      "slide_type": "subslide"
     }
    },
    "outputs": [],
    "source": [
-    "# ---------------------------------------------------------------\n",
-    "# plot\n",
+    "# Cell 2c - plot\n",
     "plt.rcParams['figure.figsize'] = 17, 17\n",
     "tx1 = 3000\n",
     "tx2 = 8000\n",
@@ -392,7 +395,7 @@
    },
    "outputs": [],
    "source": [
-    "# plot - comment single lines to better see the remaining ones\n",
+    "# Cell 3b: plot - comment single lines to better see the remaining ones\n",
     "plt.rcParams['figure.figsize'] = 15, 4\n",
     "plt.plot(t, tr.data, 'k', label='original', linewidth=1.)\n",
     "plt.plot(t, tr_filt.data, 'b', label='causal, n=2', linewidth=1.2)\n",
@@ -491,6 +494,7 @@
    },
    "outputs": [],
    "source": [
+    "# Cell 5b: plot\n",
     "plt.rcParams['figure.figsize'] = 17, 21\n",
     "fig = plt.figure()\n",
     "ax1 = fig.add_subplot(7,1,1)\n",
@@ -574,6 +578,13 @@
     "\n",
     "6) There is no clear S-wave visible. Also in the horizontal components (channel 0 and 1) almost no S-wave energy is visible. This is a clear hint for an explosive type of event. Indeed, this is the recording of a nuclear test explosion. The recording with exactly these bandpass filters was used as cover figure for the book 'Quantitative Seismology' by Keiiti Aki and Paul G. Richards, 2nd edition."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -594,6 +605,9 @@
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.7.6"
+  },
+  "rise": {
+   "scroll": true
   }
  },
  "nbformat": 4,