Analytical Framework
Mathematical manipulation of sampled data provides the means to extract and modify information represented in discrete-time sequences. The field of digital signal processing operates on the assumption that an analog input has been correctly quantized and band-limited. It provides a flexible alternative to analog circuitry by using software algorithms to perform filtering and spectral analysis.
Computational Implementation
Discrete-time systems rely on numerical representations of signals rather than continuous voltage levels. Within digital signal processing, operations such as convolution and transformation are performed by high-speed processors or dedicated hardware logic. This approach allows for the implementation of complex filters that would be impossible to build with passive electronic components.
Programmable logic enables updates to the signal chain without changing the physical circuit layout.
Processing Latency
Latency is introduced by the time required to convert signals and perform calculations. The timing of digital signal processing must be consistent to avoid jitter in the output.
Spectral Analysis
Fast Fourier transforms allow for the identification of frequency components within a complex waveform. Spectral calculations within digital signal processing provide a clear view of the signal energy distribution. Engineers manage this error by choosing appropriate word lengths for the data and the coefficients.
