Howtosignalprocessing
- What is the difference between time-domain and frequency domain signal?
- What is meant by sparse signal?
- What is sparsity in signal processing?
- Why is signal analysis performed in frequency domain than time-domain?
What is the difference between time-domain and frequency domain signal?
Put simply, a time-domain graph shows how a signal changes over time, whereas a frequency-domain graph shows how much of the signal lies within each given frequency band over a range of frequencies.
What is meant by sparse signal?
Sparse signals are characterized by a few nonzero coefficients in one of their transformation domains. This was the main premise in designing signal compression algorithms. Compressive sensing as a new approach employs the sparsity property as a precondition for signal recovery.
What is sparsity in signal processing?
A signal is considered sparse if most of its information is contained within a few non-zero samples. Consequently, a signal reconstruction algorithm has to find a sparse vector that best represents the measured signal. Many algorithms to solve this problem are based on l1-norm optimization.
Why is signal analysis performed in frequency domain than time-domain?
The frequency domain representation of a signal allows you to observe several characteristics of the signal that are either not easy to see, or not visible at all when you look at the signal in the time domain. For instance, frequency-domain analysis becomes useful when you are looking for cyclic behavior of a signal.
