Signal Processing is the analysis, interpretation, and manipulation of signals. Signals of interest include: sound, images, time-varying measurement values and sensor data. Signals can be analog or digital electrical representations of time-varying or spatial-varying physical quantities. In the context of signal processing, arbitrary binary data streams and on-off signals are not considered as signals, but only analog and digital signals that are representations of analog physical quantities.
Examples of Signal Processing:
An Infinite Impulse Response (IIR) filter is an example of a digital signal processing filter. An IIR filter outputs the weighted sum of past and current samples of input, using all past samples, but the weights of past samples are an inverse function of the sample age, approaching zero for old samples. IIR filter systems have an impulse response function that is non-zero over an infinite length of time, as opposed to a finite length of time for a finite impulse response (FIR) system.
Concurrent EDA has the capability to rapidly create signal processing cores that operate on 200 Million Samples per second (200 MS/sec) and at 1 to 100 billion operations per second. The following are completed cores that implement signal processing functions and illustrate the types of cores that Concurrent EDA can create using our automation tools.
If you don't see the core you need, fill out the short Request a Core page and we will get back to you within 24 hours or just give us a call.
