Digital signal digital data

Transmission Basics In data networking, transmit means to issue signals to the network medium Transmission refers to either the process of transmitting or the progress of signals after they have been transmitted

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Search of accessible beams for monitoring in a reception poin. Reception and processing physical channels in directions "subscriber-satellite" and "satellite-subscriber". Primary processing of the received digital signal (extraction of data packages, demultiplexing, removal of scrambler, deinterleaving,removal convolutional codings).

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The Data-over-Cable Service Interface Specification (DOCSIS)is an international standard developed by CableLabs, a non-profit research and development consortium for cable-related technologies. • DOCSIS specifies the OSI Layer 1 and Layer 2 requirements: Physical layer-For data signals that the cable operator can use, DOCSIS specifies the channel widths (bandwidths of each channel) as 200 kHz, 400 kHz, 800 kHz, 1.6 MHz, 3.2 MHz, and 6.4 MHz. DOCSIS also specifies modulation techniques (the way to use the RF signal to convey digital data).

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Digital-to-analog conversion is the process of changing one of the characteristics of an analog signal based on the information in digital data.

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In this section, we see how we can represent digital data by using digital signals. The conversion involves three techniques: line coding, block coding, and scrambling. Line coding is always needed; block coding and scrambling may or may not be needed.

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Unipolar All signal elements have same sign Polar One logic state represented by positive voltage the other by negative voltage Data rate Rate of data transmission in bits per second Duration or length of a bit Time taken for transmitter to emit the bit

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Digital signal processing has revolutionized the storage and transmission of audio and video signals as well as still images, in consumer electronics and in more scientific settings (such as medical imaging). The main advantage of digital signal processing is its robustness: although all the operations have to be implemented with, of necessity, not quite ideal hardware, the a priori knowledge that all correct outcomes must lie in a very restricted set of well-separated numbers makes it possible to recover them by rounding off appropriately. ...

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In this paper we present the implementation of a digital lock-in amplifier (LIA) completely based on Labview with a general-purpose data acquisition board (or a high quality sound card) and a high-gain low-noise amplifier. The signal analysis is processed by the software. We describe some characteristics of the LIA including output voltage vs. frequency and output phase vs. noise. The LIA can be used to measure the small signals, even in presence of broadband noise which is several times greater than the signal itself. Since the signal processing takes place on the computer, ...

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Data can be analog or digital. The term analog data refers to information that is continuous; digital data refers to information that has discrete states. Analog data take on continuous values. Digital data take on discrete values.Data can be analog or digital. Analog data are continuous and take continuous values. Digital data have discrete states and take discrete values.

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GSM is a Second Generation (2G) digital radio cellular network Time Division Multiplexing / Multiple access TDM/TDMA) are employed .Capacity necessary to transmit appropriate data signals between two access points creating an interface to the network

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Topics in Digital Communications Digital communication system advantages and disadvantages Digital communication system classification Digitization of analog signals Digital transmission systems Data communication systems Integrated Services Digital Network and other advanced digital communication systems.

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EURASIP Journal on Applied Signal Processing 2003:10, 1001–1015 c 2003 Hindawi Publishing Corporation Watermarking-Based Digital Audio Data Authentication Martin Steinebach Fraunhofer Institute IPSI, MERIT, C4M Competence for Media Security, D-64293 Darmstadt, Germany Email: martin.steinebach@ipsi.fraunhofer.de Jana Dittmann Platanista GmbH and Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany Email: jana.dittmann@iti.cs.uni-magdeburg.

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Dữ liệu tương tự, tín hiệu số • Ứng dụng – Dùng để truyền dữ liệu tương tự trên mạng truyền dữ liệu số • Tận dụng các ưu điểm của truyền dẫn số (thiết bị rẻ, dùng repeater, TDM, …) Analog and digital transmission Analog data Digital data Analog Analog signal signal Analog Analog signal signal

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A bit (binary digit) is the smallest unit of information • N = 2n where N is the number of representations and n is the number of bits (ex. ASCII, Unicode, PCM code etc.) • Data communications transfer information using codes that are transmitted as signals (either analog or digital) • In general, analog lines provide a slow service that contains high error rates.

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SAMPLING AND RECONSTRUCTION WITH INTERSAMPLE ERROR A fundamental requirement of sampled-data systems is the sampling of continuoustime signals to obtain a representative set of numbers that can be used by a digital computer. The primary goal of this chapter is to provide an understanding of this process. The first section explores theoretical aspects of sampling and the formal considerations of signal recovery, including ideal Wiener filtering in signal interpolation. Aliasing of signal and noise are considered next in a detailed development involving a heterodyne basis of evaluation. ...

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DATA CONVERSION DEVICES AND ERRORS Data conversion devices provide the interfacing components between continuoustime signals representing the parameters of physical processes and their discrete-time digital equivalent. Recent emphasis on computer systems for automated manufacturing and the growing interest in using personal computers for data acquisition and control have increased the need for improved understanding of the design requirements of real-time computer I/O systems.

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Fundamentals Adaptive systems are at the very core of modern digital signal processing. There are many reasons for this, foremost amongst these is that adaptive filtering, prediction or identification do not require explicit a priori statistical knowledge of the input data. Adaptive systems are employed in numerous areas such as biomedicine, communications, control, radar, sonar and video processing (Haykin 1996a).

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The Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar, and Medical Imaging Real-Time Systems Stergios Stergiopoulos The Transform and Data Compression Handbook K.R. Rao and P.C.

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