Questions and Answers
What is a signal?
A representation of a physical quantity that varies with respect to time or space.
Which of the following are types of signals?
What is an example of a One Dimensional (1-D) signal?
Audio Signal.
What is a Two Dimensional (2-D) signal?
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What type of signal is defined as Continuous Time Signal (CTS)?
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What is a Discrete Time Signal (DTS)?
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A Discrete Time Signal contains an infinite set of values.
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A Continuous Time Signal is represented as x(____), where t is a continuous variable.
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The process of converting a continuous-time signal into a discrete-time signal is called ____.
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What is the function of sampling in signal processing?
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Which of these is an example of a Continuous Time Signal?
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Study Notes
Definition of Signals
- Signals represent a physical quantity (e.g., sound, temperature) that changes over time or space.
- They are single-valued functions carrying information through amplitude, frequency, and phase.
- Common examples include voice signals and video signals.
Classification of Signals
- Signals can be classified based on the number of dimensions into:
- One Dimensional (1-D): Function of one variable; examples include audio and biomedical signals.
- Two Dimensional (2-D): Function of two variables; represented by image signals where intensity varies with spatial coordinates.
- Three Dimensional (3-D): Function of three variables; represented by video signals depending on spatial coordinates and time.
Types of Signals by Nature
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Continuous Time Signal (CTS):
- Values continually vary over time with an infinite set of values.
- Represented as x(t), where t is a continuous variable.
- Examples include electrical signals and temperature changes over time.
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Discrete Time Signal (DTS):
- Contains a finite set of values at specific time intervals.
- Created through sampling, which converts continuous signals into discrete form.
- Represented as x[n], where samples are taken at regular intervals Ts, with the sampling frequency fs being the reciprocal of Ts.
Operations on Signals
- Addition, multiplication, scaling, shifting, and folding are fundamental operations performed on signals.
Definition and Classification of Systems
- Systems can be defined in continuous and discrete domains, characterized by attributes:
- Linear vs. Non-Linear
- Causal vs. Non-Causal
- Stable vs. Unstable
- Time Variant vs. Time Invariant
Linear Time-Invariant (LTI) Systems
- A category of systems that maintain linearity and consistency over time, crucial for signal processing analysis.
Convolution and Correlation
- Fundamental operations used in signal processing to analyze and manipulate signals effectively.
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Description
This quiz focuses on the analysis of continuous and discrete time signals, offering insights into their definitions and classifications. Topics include periodic and aperiodic signals as well as deterministic and random signals. Perfect for students of electronics and communication looking to deepen their understanding.