I am trying to understand the process of Convolutional Neural Networks. Basically, I am trying to understand how does the local connection works. The first step of CNN is a convolution layer where every image is convolved with filters. If for example I have 100 filters, how does the local connections working? If I am understanding well, I have to convolve the input image with all 100 filters in order to produce 100 feature map in the convolutional layer. How does local connection implied in the CNN process? Where is the idea of local receptive fields implied?
EDiT: After the design of the architecture. The weights of all layers, convolutional pooling and the fully connected layer are trained by using back propagation?