[doc] minor edits to convolution layer in tutorial

docs/tutorial/layers.md

@@ -28,12 +28,12 @@ In contrast, other layers (with few exceptions) ignore the spatial structure of
 * CUDA GPU implementation: `./src/caffe/layers/convolution_layer.cu`
 * Options (`ConvolutionParameter convolution_param`)
     - Required: `num_output` (`c_o`), the number of filters
-    - Required: `kernel_size` or (`kernel_h`, `kernel_w`), specifies height & width of each filter
+    - Required: `kernel_size` (or `kernel_h` and `kernel_w`), specifies height and width of each filter
     - Strongly recommended (default `type: 'constant' value: 0`): `weight_filler`
     - Optional (default `true`): `bias_term`, specifies whether to learn and apply a set of additive biases to the filter outputs
-    - Optional (default 0): `pad` or (`pad_h`, `pad_w`), specifies the number of pixels to (implicitly) add to each side of the input
-    - Optional (default 1): `stride` or (`stride_h`, `stride_w`), specifies the intervals at which to apply the filters to the input
-    - Optional (default 1): `group` (g). If g > 1, we restrict the connectivity of each filter to a subset of the input. Specifically, the input and output channels are separated to g groups separately, and the i-th output group channels will be only connected to the i-th input group channels.
+    - Optional (default 0): `pad` (or `pad_h` and `pad_w`), specifies the number of pixels to (implicitly) add to each side of the input
+    - Optional (default 1): `stride` (or `stride_h` and `stride_w`), specifies the intervals at which to apply the filters to the input
+    - Optional (default 1): `group` (g). If g > 1, we restrict the connectivity of each filter to a subset of the input. Specifically, the input and output channels are separated into g groups, and the $$i$$th output group channels will be only connected to the $$i$$th input group channels.
 * Input
     - `n * c_i * h_i * w_i`
 * Output