Classification of Systems | Signals and Systems - Electrical Engineering (EE) PDF Download

Properties of discrete variable systems

We have classified systems into three classes - Continuous-time systems, Discrete-time systems and Hybrid systems. Now that we have introduced some system properties, let us see what properties are relevant to which classes of systems.

Let us first consider examples of different classes of systems.

Continuous-time systems
ontinuous-Continuous systems 1.Tree swaying in the wind: Wind - described by its speed, direction - is a continuous-time input. Movement of branches is continuous-time output signal.
Discrete-time systems 
Discrete-Discrete systems 1.Logic circuits: Discrete logic inputs are processed to give discrete logic outputs.
Hybrid systems 
Continuous-Discrete systems 1.Eye: sees continuous image, but sends a discrete map to the brain 2.Computer microphone: Sampler converts a continuous time signal into a discrete time signal.(Sampler forms an important system in today’s digital world - we shall look at this in great detail later in the course)
Hybrid systems 
Discrete-Continuous systems 1.Brain : gets a discrete map from the eye, and completes a smooth, continuous picture 2.Computer speaker and sound card - a digital music output given by the computer is smoothed out and played as a continuous waveform.


Properties of systems
In early parts of this course, we shall concern ourselves with mainly the first two classes, viz. Continuous-time and Discrete-time systems, but later we shall also deal with Hybrid systems as well. So, we find it worthwhile here to take a look at what properties the systems of various classes can have:

Classification of Systems | Signals and Systems - Electrical Engineering (EE)
 

Note that this is a table of properties which the system can have; they are not necessary properties of a system. Hence, we can find a Continuous-time system that is stable (though there may be Continuous-time systems which are unstable), but it is impossible to apply the concept of memory to a discrete-continuous system without modifying the concept itself.

The document Classification of Systems | Signals and Systems - Electrical Engineering (EE) is a part of the Electrical Engineering (EE) Course Signals and Systems.
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FAQs on Classification of Systems - Signals and Systems - Electrical Engineering (EE)

1. What are the different types of systems?
Ans. There are various types of systems classified based on their characteristics and functionalities. Some common types of systems include: - Physical systems: These are tangible systems composed of physical components, such as machinery, buildings, or infrastructure. - Biological systems: These are living systems, including organisms, ecosystems, or biological processes. - Social systems: These are systems involving human interactions, such as organizations, communities, or cultural systems. - Information systems: These are systems that manage and process information, including computer systems, databases, or communication networks. - Ecological systems: These are systems that involve the interactions between living organisms and their environment, such as ecosystems or natural habitats.
2. What is the purpose of system classification?
Ans. System classification helps in understanding and organizing different types of systems based on their characteristics and functionalities. It provides a framework to analyze, compare, and study systems in various fields such as engineering, biology, sociology, and information technology. Classification helps in identifying similarities and differences between systems, enabling better management, design, and decision-making processes. It also allows for the development of specialized knowledge and expertise in specific system types, leading to advancements and improvements in each domain.
3. How are systems classified based on their complexity?
Ans. Systems can be classified based on their complexity into three main categories: - Simple systems: These are straightforward systems with a small number of components or elements. They have simple relationships and interactions, making them relatively easy to understand and analyze. - Complex systems: These systems consist of numerous interconnected components or elements, often exhibiting emergent behavior and non-linear relationships. Complex systems are challenging to comprehend fully and require advanced modeling and analytical techniques for study and management. - Chaotic systems: These are highly unpredictable and sensitive systems, often characterized by extreme complexity and non-linear dynamics. Chaotic systems are difficult to control or predict accurately, making them a subject of intense research and study in fields like physics and mathematics.
4. How does system classification help in problem-solving?
Ans. System classification plays a crucial role in problem-solving by providing a structured approach to understand and analyze complex situations. By classifying a problem into a specific system type, it becomes easier to identify the relevant variables, relationships, and constraints involved. This classification enables the application of appropriate tools, methodologies, and strategies to address the problem effectively. It also helps in drawing insights and lessons from similar problems in the same system category, leading to more efficient and targeted problem-solving approaches.
5. Can a system belong to multiple classification categories simultaneously?
Ans. Yes, a system can belong to multiple classification categories simultaneously. Many real-world systems exhibit characteristics that span across different types. For example, an information system in an organization can be classified as both a social system (involving human interactions) and an information system (managing and processing data). Similarly, ecological systems can have components that belong to biological systems (living organisms) and physical systems (natural habitats). Understanding the multi-dimensional nature of systems helps in comprehending their complexity and interdependencies, leading to more accurate analysis, design, and management.
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