Signals and Systems Exploration

What are the main classifications of signals?

• Static, Dynamic

• Linear, Nonlinear

• Continuous, Discrete, Analog, Digital, Deterministic, Random, Periodic, Aperiodic

• Synchronous, Asynchronous

Define continuous-time and discrete-time signals.

• Continuous-time signals are defined for all time, while discrete-time signals are defined only at specific time intervals.

• Continuous-time signals can only be represented in digital form.

• Discrete-time signals are defined for all time and continuous-time signals are not.

• Continuous-time signals are defined only at specific time intervals.

What is the difference between analog and digital signals?

• Analog signals are faster than digital signals.

• Analog signals can only be used for audio; digital signals are for video.

• Analog signals are discrete; digital signals are continuous.

• Analog signals are continuous; digital signals are discrete.

Explain the classification of systems based on linearity.

• Linear systems and nonlinear systems

• Static systems and dynamic systems

• Deterministic systems and stochastic systems

• Discrete systems and continuous systems

What is the significance of time-invariance in systems?

• Time-invariance means inputs must be applied at specific times.

• Time-invariance is only relevant for linear systems.

• Time-invariance ensures consistent system behavior regardless of when inputs are applied.

• Time-invariance allows systems to change behavior over time.

Describe the concept of orthogonal signals.

• Orthogonal signals are dependent signals that can be combined to create new signals.

• Orthogonal signals are signals that amplify each other, resulting in a higher output.

• Orthogonal signals are always in phase with each other, leading to constructive interference.

• Orthogonal signals are independent signals that do not interfere with each other, characterized by an inner product of zero.

How do orthogonal signals relate to signal space?

• Orthogonal signals represent the same dimension in signal space.

• Orthogonal signals correspond to distinct dimensions in signal space, allowing for efficient representation and separation.

• Orthogonal signals cannot be separated in signal space.

• Orthogonal signals are identical in signal space.

What is the analogy between vectors and signals?

• Vectors are only used in physics, while signals are used in communication.

• Vectors can only represent physical quantities, whereas signals cannot.

• Both vectors and signals can be represented in a multidimensional space and analyzed using similar mathematical techniques.

• Signals are always one-dimensional, while vectors can be multi-dimensional.

Explain the concept of signal energy and power.

• Signal energy is the average energy per unit time, while signal power is the total energy in a signal over time.

• Signal energy refers to the frequency of a signal, while signal power is its amplitude.

• Signal energy is the total energy in a signal over time, while signal power is the average energy per unit time.

• Signal energy is only relevant for digital signals, while signal power applies to analog signals.

What is a linear time-invariant (LTI) system?

• A system that is nonlinear and time-variant, meaning its output is not proportional to its input.

• A system that only operates in the frequency domain and is not time-invariant.

• A system that changes its behavior based on the input signal's history.

• A system that is linear and time-invariant, meaning its output is directly proportional to its input and does not change over time.