System analysis

System analysis in the field of electrical engineering that characterizes electrical systems and their properties. System analysis can be used to represent almost anything from population growth to audio speakers; electrical engineers often use it because of its direct relevance to many areas of their discipline, most notably signal processing, communication systems and control systems.

Characterization of systems

A system is characterized by how it responds to input signals. In general, a system has one or more input signals and one or more output signals. Therefore, one natural characterization of systems is by how many inputs and outputs they have:

  • SISO (Single Input, Single Output)
  • SIMO (Single Input, Multiple Outputs)
  • MISO (Multiple Inputs, Single Output)
  • MIMO (Multiple Inputs, Multiple Outputs)

It is often useful (or necessary) to break up a system into smaller pieces for analysis. Therefore, we can regard a SIMO system as multiple SISO systems (one for each output), and similarly for a MIMO system. By far, the greatest amount of work in system analysis has been with SISO systems, although many parts inside SISO systems have multiple inputs (such as adders).

Signals can be continuous or discrete in time, as well as continuous or discrete in the values they take at any given time:

  • Signals that are continuous in time and continuous in value are known as analog signals.
  • Signals that are discrete in time and discrete in value are known as digital signals.
  • Signals that are discrete in time and continuous in value are called discrete-time signals. Switched capacitor systems, for instance, are often used in integrated circuits. The methods developed for analyzing discrete time signals and systems are usually applied to digital and analog signals and systems.
  • Signals that are continuous in time and discrete in value are sometimes seen in the timing analysis of logic circuits or PWM amplifiers, but have little to no use in system analysis.

With this categorization of signals, a system can then be characterized as to which type of signals it deals with:

  • A system that has analog input and analog output is known as an analog system.
  • A system that has digital input and digital output is known as a digital system.
  • Systems with analog input and digital output or digital input and analog output are possible. However, it is usually easiest to break these systems up for analysis into their analog and digital parts, as well as the necessary analog to digital or digital to analog converter.

Another way to characterize systems is by whether their output at any given time depends only on the input at that time or perhaps on the input at some time in the past (or in the future!).

  • Memoryless systems do not depend on any past input. In common usage memoryless systems are also independent of future inputs. An interesting consequence of this is that the impulse response of any memoryless system is itself a scaled impulse.
  • Systems with memory do depend on past input.
  • Causal systems do not depend on any future input.
  • Non-causal or anticipatory systems do depend on future input.
    Note: It is not possible to physically realize a non-causal system operating in "real time". However, from the standpoint of analysis, they are important for two reasons. First, the ideal system for a given application is often a noncausal system, which although not physically possible can give insight into the design of a derived causal system to accomplish a similar purpose. Second, there are instances when a system does not operate in "real time" but is rather simulated "off-line" by a computer, such as post-processing an audio or video recording.
    Further, some non-causal systems can operate in pseudo-real time by introducing lag: if a system depends on input for 1 second in future, it can process in real time with 1 second lag.

Analog systems with memory may be further classified as lumped or distributed. The difference can be explained by considering the meaning of memory in a system. Future output of a system with memory depends on future input and a number of state variables, such as values of the input or output at various times in the past. If the number of state variables necessary to describe future output is finite, the system is lumped; if it is infinite, the system is distributed.

Finally, systems may be characterized by certain properties which facilitate their analysis:

  • A system is linear if it has the superposition and scaling properties. A system that is not linear is non-linear.
  • If the output of a system does not depend explicitly on time, the system is said to be time-invariant; otherwise it is time-variant
  • A system that will always produce the same output for a given input is said to be deterministic.
  • A system that will produce different outputs for a given input is said to be stochastic.

There are many methods of analysis developed specifically for linear time-invariant (LTI) deterministic systems. Unfortunately, in the case of analog systems, none of these properties are ever perfectly achieved. Linearity implies that operation of a system can be scaled to arbitrarily large magnitudes, which is not possible. Time-invariance is violated by aging effects that can change the outputs of analog systems over time (usually years or even decades). Thermal noise and other random phenomena ensure that the operation of any analog system will have some degree of stochastic behavior. Despite these limitations, however, it is usually reasonable to assume that deviations from these ideals will be small.

LTI Systems

As mentioned above, there are many methods of analysis developed specifically for LTI systems. This is due to their simplicity of specification. An LTI system is completely specified by its transfer function (which is a rational function for digital and lumped analog LTI systems). Alternatively, we can think of an LTI system being completely specified by its frequency response. A third way to specify an LTI system is by its characteristic linear differential equation (for analog systems) or linear difference equation (for digital systems). Which description is most useful depends on the application.

The distinction between lumped and distributed LTI systems is important. A lumped LTI system is specified by a finite number of parameters, be it the zeros and poles of its transfer function, or the coefficients of its differential equation, whereas specification of a distributed LTI system requires a complete function

See also

Important concepts in system analysis

Related fields

Admittance

In electrical engineering, admittance is a measure of how easily a circuit or device will allow a current to flow. It is defined as the reciprocal of impedance. The SI unit of admittance is the siemens (symbol S); the older, synonymous unit is mho, and its symbol is ℧ (an upside-down uppercase omega Ω). Oliver Heaviside coined the term admittance in December 1887.

Admittance is defined as

where

Y is the admittance, measured in siemens
Z is the impedance, measured in ohms

Resistance is a measure of the opposition of a circuit to the flow of a steady current, while impedance takes into account not only the resistance but also dynamic effects (known as reactance). Likewise, admittance is not only a measure of the ease with which a steady current can flow, but also the dynamic effects of the material's susceptance to polarization:

where

Automatic Generation Control

In an electric power system, automatic generation control (AGC) is a system for adjusting the power output of multiple generators at different power plants, in response to changes in the load. Since a power grid requires that generation and load closely balance moment by moment, frequent adjustments to the output of generators are necessary. The balance can be judged by measuring the system frequency; if it is increasing, more power is being generated than used, which causes all the machines in the system to accelerate. If the system frequency is decreasing, more load is on the system than the instantaneous generation can provide, which causes all generators to slow down.

Chengdu University of Information Technology

Chengdu University of Information Technology (CUIT, Chinese: 成都信息工程大学) is a provincial key university co-governed and co-sponsored by China Meteorological Administration and Sichuan Province in Chengdu, Sichuan, China.CUIT is a leading university in the scientific research and technological application of the interdisciplinary integration of atmospheric science and information technology, and a member of CDIO Initiative world organization. Since 2004, CUIT has begun educating reserve army officers for People's Liberation Army Rocket Force,the strategic and tactical missile forces of the People's Republic of China.In recent years, CUIT has been granted 123 state-level scientific research projects including National Science and Technology Plan, National Natural Science Fund projects, and National Social Science Fund projects, obtaining science and technology funds about 58.2 million RMB annually; 46 provincial and ministerial science awards, 2 of which are National Science and Technology Progress Awards (second class); 3315 academic papers have been published, with 910 articles cited by the important retrieval system SCI, and over 100 articles on influential journals from both in and abroad.CUIT has 8 key provincial and ministerial laboratories(including Sichuan Engineering and Technological Research Center, Sichuan key Research Bases for Philosophy and Social Sciences), 7 key laboratories supervised by universities and Research Bases for Humanities and Social Sciences, and 1 post-doctoral research station. CUIT has reached advanced world standards in the research of new-type weather radar system, China Doppler weather radar of a new generation, atmospheric radiation and satellite remote sensing, weather dynamics and dry monsoon, environmental system analysis and environmental monitoring & evaluation, computer and software, information security, and E-commerce.

Cybernetics

Cybernetics is a transdisciplinary approach for exploring regulatory systems—their structures, constraints, and possibilities. Norbert Wiener defined cybernetics in 1948 as "the scientific study of control and communication in the animal and the machine." In the 21st century, the term is often used in a rather loose way to imply "control of any system using technology." In other words, it is the scientific study of how humans, animals and machines control and communicate with each other.

Cybernetics is applicable when a system being analyzed incorporates a closed signaling loop—originally referred to as a "circular causal" relationship—that is, where action by the system generates some change in its environment and that change is reflected in the system in some manner (feedback) that triggers a system change. Cybernetics is relevant to, for example, mechanical, physical, biological, cognitive, and social systems. The essential goal of the broad field of cybernetics is to understand and define the functions and processes of systems that have goals and that participate in circular, causal chains that move from action to sensing to comparison with desired goal, and again to action. Its focus is how anything (digital, mechanical or biological) processes information, reacts to information, and changes or can be changed to better accomplish the first two tasks. Cybernetics includes the study of feedback, black boxes and derived concepts such as communication and control in living organisms, machines and organizations including self-organization.

Concepts studied by cyberneticists include, but are not limited to: learning, cognition, adaptation, social control, emergence, convergence, communication, efficiency, efficacy, and connectivity. In cybernetics these concepts (otherwise already objects of study in other disciplines such as biology and engineering) are abstracted from the context of the specific organism or device.

The word cybernetics comes from Greek κυβερνητική (kybernētikḗ), meaning "governance", i.e., all that are pertinent to κυβερνάω (kybernáō), the latter meaning "to steer, navigate or govern", hence κυβέρνησις (kybérnēsis), meaning "government", is the government while κυβερνήτης (kybernḗtēs) is the governor or "helmperson" of the "ship". Contemporary cybernetics began as an interdisciplinary study connecting the fields of control systems, electrical network theory, mechanical engineering, logic modeling, evolutionary biology, neuroscience, anthropology, and psychology in the 1940s, often attributed to the Macy Conferences. During the second half of the 20th century cybernetics evolved in ways that distinguish first-order cybernetics (about observed systems) from second-order cybernetics (about observing systems). More recently there is talk about a third-order cybernetics (doing in ways that embraces first and second-order).Studies in cybernetics provide a means for examining the design and function of any system, including social systems such as business management and organizational learning, including for the purpose of making them more efficient and effective. Fields of study which have influenced or been influenced by cybernetics include game theory, system theory (a mathematical counterpart to cybernetics), perceptual control theory, sociology, psychology (especially neuropsychology, behavioral psychology, cognitive psychology), philosophy, architecture, and organizational theory. System dynamics, originated with applications of electrical engineering control theory to other kinds of simulation models (especially business systems) by Jay Forrester at MIT in the 1950s, is a related field.

Data warehouse automation

Data warehouse automation (DWA) refers to the process of accelerating and automating the data warehouse development cycles, while assuring quality and consistency. DWA is believed to provide automation of the entire lifecycle of a data warehouse, from source system analysis to testing to documentation. It helps improve productivity, reduce cost, and improve overall quality.

Earth system science

Earth system science (ESS) is the application of systems science to the Earth sciences. In particular, it considers interactions between the Earth's "spheres"—atmosphere, hydrosphere, cryosphere, geosphere, pedosphere, biosphere, and, even, the magnetosphere—as well as the impact of human societies on these components. At its broadest scale, Earth system science brings together researchers across both the natural and social sciences, from fields including ecology, economics, geology, glaciology, meteorology, oceanography, paleontology, sociology, and space science. Like the broader subject of systems science, Earth system science assumes a holistic view of the dynamic interaction between the Earth's spheres and their many constituent subsystems, the resulting organization and time evolution of these systems, and their stability or instability. Subsets of Earth system science include systems geology and systems ecology, and many aspects of Earth system science are fundamental to the subjects of physical geography and climate science.

Edith Clarke

Edith Clarke (February 10, 1883 – October 29, 1959) was the first female electrical engineer and the first female professor of electrical engineering at the University of Texas at Austin. She specialized in electrical power system analysis and wrote Circuit Analysis of A-C Power Systems.

FF Aquilae

FF Aquilae is a classical Cepheid variable star located in the constellation Aquila. It ranges from apparent magnitude 5.18 to 5.51 over a period of 4.470848 days, meaning it is faintly visible to the unaided eye in rural or suburban settings. Originally known as HR 7165, it was noted to be variable by Charles Morse Huffer in August 1927, who observed its Cepheid pattern. It then received the variable star designation FF Aquilae. Analysis of its brightness over 122 years shows that its period is increasing by 0.072 ± 0.011 seconds per year. It has been estimated to be 1,350 light-years (413 parsecs) ± 46 light-years (14 parsecs) distant from Earth (by extrapolating from its angular diameter and estimated radius).A yellow supergiant, FF Aql pulsates with varying temperature, diameter, and luminosity. Like all Cepheids, it has exhausted its core hydrogen fuel, cooled and expanded off the main sequence, and is rapidly evolving towards the Asymptotic Giant Branch.

FF Aql is a possible quadruple star system. Analysis of its spectrum shows that it is a spectroscopic binary system with the fainter companion calculated to be a main sequence star of spectral type A9V to F3V, orbiting every 3.92 years. A third star, revealed by speckle interferometry, is likely to be a cooler star that has evolved off the main sequence. A fourth star, that is of magnitude 11.4 and located 6 arcseconds away, is unlikely to be a member of the system.

Heat transfer

Heat transfer is a discipline of thermal engineering that concerns the generation, use, conversion, and exchange of thermal energy (heat) between physical systems. Heat transfer is classified into various mechanisms, such as thermal conduction, thermal convection, thermal radiation, and transfer of energy by phase changes. Engineers also consider the transfer of mass of differing chemical species, either cold or hot, to achieve heat transfer. While these mechanisms have distinct characteristics, they often occur simultaneously in the same system.

Heat conduction, also called diffusion, is the direct microscopic exchange of kinetic energy of particles through the boundary between two systems. When an object is at a different temperature from another body or its surroundings, heat flows so that the body and the surroundings reach the same temperature, at which point they are in thermal equilibrium. Such spontaneous heat transfer always occurs from a region of high temperature to another region of lower temperature, as described in the second law of thermodynamics.

Heat convection occurs when bulk flow of a fluid (gas or liquid) carries heat along with the flow of matter in the fluid. The flow of fluid may be forced by external processes, or sometimes (in gravitational fields) by buoyancy forces caused when thermal energy expands the fluid (for example in a fire plume), thus influencing its own transfer. The latter process is often called "natural convection". All convective processes also move heat partly by diffusion, as well. Another form of convection is forced convection. In this case the fluid is forced to flow by use of a pump, fan or other mechanical means.

Thermal radiation occurs through a vacuum or any transparent medium (solid or fluid or gas). It is the transfer of energy by means of photons in electromagnetic waves governed by the same laws.

Industrial engineering

Industrial engineering is an inter-disciplinary profession that is concerned with the optimization of complex processes, systems, or organizations by developing, improving and implementing integrated systems of people, money, knowledge, information, equipment, energy and materials.

Industrial engineers use specialized knowledge and skills in the mathematical, physical, and social sciences, together with the principles and methods of engineering analysis and design, to specify, predict, and evaluate the results obtained from systems and processes. From these results, they are able to create new systems, processes or situations for the useful coordination of man, materials and machines and also improve the quality and productivity of systems, physical or social. Depending on the sub-specialties involved, industrial engineering may also overlap with, operations research, systems engineering, manufacturing engineering, production engineering, management science, management engineering, financial engineering, ergonomics or human factors engineering, safety engineering, or others, depending on the viewpoint or motives of the user.

Even though its underlying concepts overlap considerably with certain business-oriented disciplines, such as operations management, industrial engineering is a longstanding engineering discipline subject to (and eligible for) professional engineering licensure in most jurisdictions.

Lumped element model

The lumped element model (also called lumped parameter model, or lumped component model) simplifies the description of the behaviour of spatially distributed physical systems into a topology consisting of discrete entities that approximate the behaviour of the distributed system under certain assumptions. It is useful in electrical systems (including electronics), mechanical multibody systems, heat transfer, acoustics, etc.

Mathematically speaking, the simplification reduces the state space of the system to a finite dimension, and the partial differential equations (PDEs) of the continuous (infinite-dimensional) time and space model of the physical system into ordinary differential equations (ODEs) with a finite number of parameters.

Measurement system analysis

A measurement systems analysis (MSA) is a through assessment of a

measurement process,

and typically includes a specially designed experiment that seeks to identify the components of variation in that measurement process.

Just as processes that produce a product may vary,

the process of obtaining measurements and data may also have variation and produce incorrect results.

A measurement systems analysis evaluates the test method, measuring instruments, and the entire process of obtaining measurements to ensure the integrity of data used for analysis (usually quality analysis) and to understand the implications of measurement error for decisions made about a product or process.

MSA is an important element of Six Sigma methodology and of other quality management systems.

MSA analyzes the collection of equipment, operations, procedures, software and personnel that affects the assignment of a number to a measurement characteristic.

A measurement systems analysis considers the following:

Selecting the correct measurement and approach

Assessing the measuring device

Assessing procedures and operators

Assessing any measurement interactions

Calculating the measurement uncertainty of individual measurement devices and/or measurement systemsCommon tools and techniques of measurement systems analysis include: calibration studies, fixed effect ANOVA, components of variance, attribute gage study, gage R&R, ANOVA gage R&R, and destructive testing analysis.

The tool selected is usually determined by characteristics of the measurement system itself.

An introduction to MSA can be found in chapter 8 of Doug Montgomery's Quality Control book.

These tools and techniques are also described in the books by Donald Wheeler

and Kim Niles.

Advanced procedures for designing MSA studies can be found in Burdick et. al.

Mykhailo Zghurovsky

Mykhailo Zakharovych Zghurovskyi (Ukrainian: Михайло Захарович Згуровський, Michael Zakharovich Zgurovsky; born 30 January 1950) is a Ukrainian scientist. Mykhailo Zghurovsky is the President of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Scientific Supervisor of the Institute for Applied System Analysis (part of both Ministry of Education and Science of Ukraine and National Academy of Sciences of Ukraine), former Ukrainian education minister.

Mykhailo Zghurovsky is a scientist in the fields of mathematics and System analysis. His research focuses in methodology of system analysis, theory of decision making under uncertainty conditions, analysis and modeling of complex systems of various natures.

NUST School of Electrical Engineering and Computer Science

NUST School of Electrical Engineering and Computer Science (NUST-SEECS), formerly NUST Institute of Information Technology, is a constituent school located in Islamabad, Pakistan. NUST-SEECS was launched on self-finance basis in April 1999 as a constituent college of National University of Sciences and Technology, Pakistan (NUST). It was formed due to the demand for quality IT education in the country and the requirement for NUST to launch its own IT department.

Sex-determination system

A sex-determination system is a biological system that determines the development of sexual characteristics in an organism. Most organisms that create their offspring using sexual reproduction have two sexes. Occasionally, there are hermaphrodites in place of one or both sexes. There are also some species that are only one sex due to parthenogenesis, the act of a female reproducing without fertilization.

In many species, sex determination is genetic: males and females have different alleles or even different genes that specify their sexual morphology. In animals this is often accompanied by chromosomal differences, generally through combinations of XY, ZW, XO, ZO chromosomes, or haplodiploidy. The sexual differentiation is generally triggered by a main gene (a "sex locus"), with a multitude of other genes following in a domino effect.

In other cases, sex of a fetus is determined by environmental variables (such as temperature). The details of some sex-determination systems are not yet fully understood. Hopes for future fetal biological system analysis include complete-reproduction-system initialized signals that can be measured during pregnancies to more accurately determine whether a determined sex of a fetus is male, or female. Such analysis of biological systems could also signal whether the fetus is hermaphrodite, which includes total or partial of both male and female reproduction organs.

Some species such as various plants and fish do not have a fixed sex, and instead go through life cycles and change sex based on genetic cues during corresponding life stages of their type. This could be due to environmental factors such as seasons and temperature. Human fetus genitals can sometimes develop abnormalities during maternal pregnancies due to mutations in the fetuses sex-determinism system, resulting in the fetus becoming intersex.

Systems analysis

The Merriam-Webster dictionary defines system analysis as "the process of studying a procedure or business in order to identify its goals and purposes and create systems and procedures that will achieve them in an efficient way". Another view sees system analysis as a problem-solving technique that breaks down a system into its component pieces for the purpose of the studying how well those component parts work and interact to accomplish their purpose.The field of system analysis relates closely to requirements analysis or to operations research. It is also "an explicit formal inquiry carried out to help a decision maker identify a better course of action and make a better decision than she might otherwise have made."The terms analysis and synthesis stem from Greek, meaning "to take apart" and "to put together," respectively. These terms are used in many scientific disciplines, from mathematics and logic to economics and psychology, to denote similar investigative procedures. Analysis is defined as "the procedure by which we break down an intellectual or substantial whole into parts," while synthesis means "the procedure by which we combine separate elements or components in order to form a coherent whole." System analysis researchers apply methodology to the systems involved, forming an overall picture.

System analysis is used in every field where something is developed. Analysis can also be a series of components that perform organic functions together, such as system engineering. System engineering is an interdisciplinary field of engineering that focuses on how complex engineering projects should be designed and managed.

Systems analyst

A systems analyst is an information technology (IT) professional who specializes in analyzing, designing and implementing information systems. Systems analysts assess the suitability of information systems in terms of their intended outcomes and liaise with end users, software vendors and programmers in order to achieve these outcomes. A systems analyst is a person who uses analysis and design techniques to solve business problems using information technology. Systems analysts may serve as change agents who identify the organizational improvements needed, design systems to implement those changes, and train and motivate others to use the systems.Although they may be familiar with a variety of programming languages, operating systems, and computer hardware platforms, they do not normally involve themselves in the actual hardware or software development. They may be responsible for developing cost analysis, design considerations, staff impact amelioration, and implementation timelines.

A systems analyst is typically confined to an assigned or given system and will often work in conjunction with a business analyst. These roles, although having some overlap, are not the same. A business analyst will evaluate the business need and identify the appropriate solution and, to some degree, design a solution without diving too deep into its technical components, relying instead on a systems analyst to do so. A systems analyst will often evaluate and modify code as well as review scripting.

Some dedicated professionals possess practical knowledge in both areas (business and systems analysis) and manage to successfully combine both of these occupations, effectively blurring the line between business analyst and systems analyst.

Systems design

Systems design is the process of defining the architecture, modules, interfaces, and data for a system to satisfy specified requirements. Systems design could be seen as the application of systems theory to product development. There is some overlap with the disciplines of systems analysis, systems architecture and systems engineering.

São Paulo State Technological College

The São Paulo State Faculty of Technology or FATECs (Portuguese: Faculdades de Tecnologia do Estado de São Paulo) are public institutions of higher education belonging to CEETEPS (State Center of Technological Education), governmental maintainer. The FATECs are important Brazilian institutions of higher education, being pioneers in the graduation of technologists. They are located in several cities of the São Paulo state, with three campuses in the capital (Bom Retiro, East Zone and South Zone), and several other units in the metropolitan region of São Paulo, countryside and seashore.

The 46 FATECs offer high degree careers in virtually all areas of knowledge. In most of the units, are offered courses of higher education in technology, focused in the training of technologists. The units of São Caetano do Sul, Ourinhos, Carapicuíba and Americana, however, offer the option of bachelorship and licentiate degree in the career of System Analysis and Information Technology, starting the tradition of FATECs to train, too, bachelors and licentiates.

More than 28 thousand students are currently enrolled in FATECs. For the formation of this quota is annually invested more than R$1 billion (US$420,000 mi).

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