Signal Processing Index

Some Ideas

Unit 1: Efficient Representation of Signal (i.e. compression)—we ideally want the smallest sequence of bits to encode the raw signal
Unit 2: Preserving Information of Signal (i.e. communication)—we ideally want to communicate our bits while not sacrificing information despite all communication channels being noisy

compress the same exactly information into less space (lossless compression)
- what is information (probability and entropy)
- compression and limits of compression (Huffman Coding)
removing irrelevant/uninteresting information (lossy compression)
- key idea: “frequency domain can be aggressively compressed”
- signals, frequency representation, bandwidth (discrete cosine transform)
- quantization, sampling, reconstruction (encoding analog signal into digital signal)

communication basics (channels and noise)
representing bits for physical/analogue communication (modulation—encoding digital signal into analog signal)
bandwidth, spectrum shaping/sharing (frequency-domain filtering)
fundamental limits (channel capacity)
separation of compression and communication (separation principle)
adding redundancy to communication schemes (error-correcting codes)