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Category# Digital electronics

Summary

Digital electronics is a field of electronics involving the study of digital signals and the engineering of devices that use or produce them. This is in contrast to analog electronics and analog signals.
Digital electronic circuits are usually made from large assemblies of logic gates, often packaged in integrated circuits. Complex devices may have simple electronic representations of Boolean logic functions.
The binary number system was refined by Gottfried Wilhelm Leibniz (published in 1705) and he also established that by using the binary system, the principles of arithmetic and logic could be joined. Digital logic as we know it was the brain-child of George Boole in the mid 19th century. In an 1886 letter, Charles Sanders Peirce described how logical operations could be carried out by electrical switching circuits. Eventually, vacuum tubes replaced relays for logic operations. Lee De Forest's modification of the Fleming valve in 1907 could be used as an AND gate. Ludwig Wittgenstein introduced a version of the 16-row truth table as proposition 5.101 of Tractatus Logico-Philosophicus (1921). Walther Bothe, inventor of the coincidence circuit, shared the 1954 Nobel Prize in physics, for creating the first modern electronic AND gate in 1924.
Mechanical analog computers started appearing in the first century and were later used in the medieval era for astronomical calculations. In World War II, mechanical analog computers were used for specialized military applications such as calculating torpedo aiming. During this time the first electronic digital computers were developed, with the term digital being proposed by George Stibitz in 1942. Originally they were the size of a large room, consuming as much power as several hundred modern PCs.
The Z3 was an electromechanical computer designed by Konrad Zuse. Finished in 1941, it was the world's first working programmable, fully automatic digital computer. Its operation was facilitated by the invention of the vacuum tube in 1904 by John Ambrose Fleming.

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Inverter (logic gate)

In digital logic, an inverter or NOT gate is a logic gate which implements logical negation. It outputs a bit opposite of the bit that is put into it. The bits are typically implemented as two differing voltage levels. The NOT gate outputs a zero when given a one, and a one when given a zero. Hence, it inverts its inputs. Colloquially, this inversion of bits is called "flipping" bits. As with all binary logic gates, other pairs of symbols such as true and false, or high and low may be used in lieu of one and zero.

Logic family

In computer engineering, a logic family is one of two related concepts: A logic family of monolithic digital integrated circuit devices is a group of electronic logic gates constructed using one of several different designs, usually with compatible logic levels and power supply characteristics within a family. Many logic families were produced as individual components, each containing one or a few related basic logical functions, which could be used as "building-blocks" to create systems or as so-called "glue" to interconnect more complex integrated circuits.

Analytical engine

The analytical engine was a proposed mechanical general-purpose computer designed by English mathematician and computer pioneer Charles Babbage. It was first described in 1837 as the successor to Babbage's difference engine, which was a design for a simpler mechanical calculator. The analytical engine incorporated an arithmetic logic unit, control flow in the form of conditional branching and loops, and integrated memory, making it the first design for a general-purpose computer that could be described in modern terms as Turing-complete.

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Logic Systems: Karnaugh Maps and TTL GatesEE-110: Logic systems (for MT)

Explores Karnaugh maps, TTL gates, analog aspects of digital logic, and prime implicants.

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Explores logic gates, hazard elimination, ALUs, counters, and shift registers in semiconductor technology.

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Microprocessors

A microprocessor is a computer processor where the data processing logic and control is included on a single integrated circuit (IC), or a small number of ICs. The microprocessor contains the arithmetic, logic, and control circuitry required to perform the functions of a computer's central processing unit (CPU). The IC is capable of interpreting and executing program instructions and performing arithmetic operations.

Topics in arithmetic

Arithmetic () is an elementary part of mathematics that consists of the study of the properties of the traditional operations on numbers—addition, subtraction, multiplication, division, exponentiation, and extraction of roots. In the 19th century, Italian mathematician Giuseppe Peano formalized arithmetic with his Peano axioms, which are highly important to the field of mathematical logic today.

Boolean logic

In mathematics and mathematical logic, Boolean algebra is a branch of algebra. It differs from elementary algebra in two ways. First, the values of the variables are the truth values true and false, usually denoted 1 and 0, whereas in elementary algebra the values of the variables are numbers. Second, Boolean algebra uses logical operators such as conjunction (and) denoted as ∧, disjunction (or) denoted as ∨, and the negation (not) denoted as ¬.

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2021Les modèles de simulation de la qualité de l'air sont des outils indispensables à la conception de stratégies de réduction de la pollution atmosphérique. Ils ont l'avantage de pouvoir calculer les effets de n'importe quelle réduction d'émissions mais présentent l'inconvénient de demander un temps de calcul très important (plusieurs jours ou semaines). Les modèles Sources/Récepteurs s'appuient sur un nombre réduit de scénarios simulés par un modèle de qualité l'air afin de pouvoir calculer très rapidement (quelques minutes) les effets de n'importe quelle réduction des émissions. Ce travail de diplôme se propose d'améliorer la nouvelle génération de modèles Sources/Récepteurs récemment développés au European Joint Research Center (JRC) d'Ispra (Italie).

2017Anastasia Ailamaki, Viktor Sanca

As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often considered a second-class citizen. Modern analytical engines optimized for high bandwidth media and multi-core architectures only exacerbate existing inefficiencies, resulting in prohibitive query-time online sampling and longer preprocessing times in offline AQP systems. We demonstrate that the sampling operators can be practical in modern scale-up analytical systems. First, we evaluate three common sampling methods, identify algorithmic bottlenecks, and propose hardware-conscious optimizations. Second, we reduce the performance penalties of the added processing and sample materialization through system-aware operator design and compare the sample creation time to the matching relational operators of an in-memory JIT-compiled engine. The cost of data reduction with materialization is up to 2.5x of the equivalent group-by in the case of stratified sampling and virtually free (∼1x) for reasonable sample sizes of other strategies. As query processing starts to dominate the execution time, the gap between online and offline AQP methods diminishes.