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Number Systems
Published in Mike Tooley, Aircraft Digital Electronic and Computer Systems, 2023
The signals in digital logic and computer systems are conveyed along individual electrical conductors and also using multiple wiring arrangements where several conductors are used to convey signals from one place to another in what is known as a bus system. As we will see in Chapter 4, the number of individual bus lines depends on the particular bus standard employed; however, signals on the individual lines, no matter what they are used for or how they are organised, can exist in only two basic states: logic 0 (‘low’ or ‘off’) or logic 1 (‘high’ or ‘on’). Thus information within a digital system is represented in the form of a sequence of 1s and 0s, known as binary data.
Introduction to Digital Systems
Published in Dale Patrick, Stephen Fardo, Vigyan ‘Vigs’ Chandra, Electronic Digital System Fundamentals, 2020
Dale Patrick, Stephen Fardo, Vigyan ‘Vigs’ Chandra
There are two basic types of logic circuits in a digital system. One type of logic circuit is designed to make decisions. It has data applied to its input and produces an output that coincides with a prescribed combination of rules. Electronic decisions are made with logic gates. Memory is the other type of logic circuit. Memory circuits store binary data. These data can be stored and retrieved from memory when the need arises. Special ICs are used to achieve the memory function of a digital system. Memory is a primary function of a digital system. Performance is largely dependent on the capacity of a system’s memory.
Introductory Concept
Published in Partha Pratim Sahu, Fundamentals of Optical Networks and Components, 2020
Binary data bits after obtaining from ASCII coder are required to encode with the digital signal, which is a sequence of discrete, discontinuous voltage pulses. Binary data are transmitted by encoding each data bit into signal elements so that there should be one-to-one correspondence between bits and signal elements. Different kinds of digital to digital encoder [33] are – NRZ-L, not return to zero inverted (NRZI), bipolar AMI, Pseudo ternary AMI, Manchester, differential Manchester, B8ZS and HDB3 [33].
Analysis of energy harvesting in SWIPT using bio-inspired algorithms
Published in International Journal of Electronics, 2023
The effect of the IQ imbalance is prominent in QAM schemes because the constellation is sensitive to symbol rotation and interference between I and Q branches. So here we consider the SWIPT system with different M-ary schemes namely 4-QAM, 8-QAM, 16-QAM and 32-QAM. The number of binary data taken = with sample time and samples per frame = . All the algorithms are evaluated based on Monte Carlo simulations with parameters . The will be calculated based on the M-ary value according to the modulation scheme. The variables will be chosen randomly by bio-inspired algorithms with as the bounds. Each of the channel is an i.i.d. Rayleigh fading parameter, which is randomly generated.
Impact of Privacy Protection on Service Platform Consumers’ Adoption Behaviour based on the Background of Big Data
Published in IETE Journal of Research, 2022
There are usually three methods for calculating the distance between records using continuous data: Manhattan distance, Euclidean distance, and Chebyshev distance. These three methods can be uniformly expressed by Minkowski distance: Among them, and are any two n-dimensional data objects in the data table, and respectively represent the n-th dimension attribute value of the i-th record and the j-th record [4–5]. The most commonly used is Euclidean distance, and its calculation formula is shown in (2): When calculating the centroid of continuous data, it is generally selected to calculate the arithmetic mean of all records. Assuming that represents the centroid in the i-th equivalence class, the calculation formula is as shown in (3): where k represents the total number of all records in the equivalence class [6–7]. Binary data distance measurement method:
A new data encoding based on maximum to minimum histogram in reversible data hiding
Published in The Imaging Science Journal, 2019
To reconstruct the hidden data, estimate the difference using equation (4)From the difference, estimate the decimal value using equation (5) and then convert the decimal values into binary to get the recovered data.To obtain the original cover image from the two stego image use equation (6)Figure 4 shows the data extraction using Centre Folding Strategy. Let the stego images are and . From the two stego images and estimate the difference using equation (4) as . From the difference estimate the decimal value by incrementing to using equation (5). The decimal value is calculated as . Converting the decimal value to ‘3 bit’ binary data as ‘110101111001’. The original cover image can be reconstructed using equation (6) as .