The state space or the internal description of the system still involves a relationship between the input and output signals, what are the additional set of variables it also involves?

Discrete Time Systems Implementation topics include: Realization structures for discrete time systems, FIR system structures, IIR system structures, number representation, state space system analysis, quantization error analysis and bilinear transformations. Discrete-time systems process discrete-time signals. They can be represented by a set of difference equations or a block diagram of their implementation.  The input and output of a discrete-time system are related by a linear constant coefficient difference equation. This equation defines a sequence of operations to implement the... Show more

Discrete Time Systems Implementation topics include: Realization structures for discrete time systems, FIR system structures, IIR system structures, number representation, state space system analysis, quantization error analysis and bilinear transformations.

Discrete-time systems process discrete-time signals. They can be represented by a set of difference equations or a block diagram of their implementation. 

The input and output of a discrete-time system are related by a linear constant coefficient difference equation. This equation defines a sequence of operations to implement the system. 
A discrete-time system is causal if the output is 0 when the input is 0 and there are no initial conditions. The output does not depend on future inputs. 
Discrete-time systems can be of finite impulse response (FIR) or infinite impulse response (IIR) type. A FIR filter is a filter whose impulse response is of finite duration. 
Before implementation, it is recommended to use a simulator of the system to test the importance of the value of h. 
Discrete-time signal processing (DSP) has applications in many domains, such as digital communications, medical imaging, audio and video systems, consumer electronics, and robotics

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