Computer Science: An OverviewTenth Edition

by J. Glenn Brookshear

Chapter 1:Data Storage

Chapter 1: Data Storage1.1 Bits and Their Storage1.2 Main Memory1.3 Mass Storage1.4 Representing Information as Bit Patterns1.5 The Binary System

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Chapter 1: Data Storage (continued)

1.6 Storing Integers1.7 Storing Fractions1.8 Data Compression1.9 Communications Errors

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Bits and Bit PatternsBit: Binary Digit (0 or 1)Bit Patterns are used to represent

information.NumbersText charactersImagesSoundAnd others

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Boolean OperationsBoolean Operation: An operation that

manipulates one or more true/false valuesSpecific operations

ANDORXOR (exclusive or)NOT

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Figure 1.1 The Boolean operations AND, OR, and XOR (exclusive or)

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GatesGate: A device that computes a Boolean

operationOften implemented as (small) electronic

circuitsProvide the building blocks from which

computers are constructedVLSI (Very Large Scale Integration)

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Figure 1.2 A pictorial representation of AND, OR, XOR, and NOT gates as well as their input and output values

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Flip-flopsFlip-flop: A circuit built from gates that can

store one bit.One input line is used to set its stored value to 1One input line is used to set its stored value to 0While both input lines are 0, the most recently

stored value is preserved

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Figure 1.3 A simple flip-flop circuit

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Figure 1.4 Setting the output of a flip-flop to 1

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Figure 1.5 Another way of constructing a flip-flop

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Hexadecimal NotationHexadecimal notation: A shorthand

notation for long bit patternsDivides a pattern into groups of four bits eachRepresents each group by a single symbol

Example: 10100011 becomes A3

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Figure 1.6 The hexadecimal coding system

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Main Memory CellsCell: A unit of main memory (typically 8

bits which is one byte)Most significant bit: the bit at the left (high-

order) end of the conceptual row of bits in a memory cell

Least significant bit: the bit at the right (low-order) end of the conceptual row of bits in a memory cell

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Figure 1.7 The organization of a byte-size memory cell

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Main Memory AddressesAddress: A “name” that uniquely

identifies one cell in the computer’s main memoryThe names are actually numbers.These numbers are assigned consecutively

starting at zero.Numbering the cells in this manner associates

an order with the memory cells.

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Figure 1.8 Memory cells arranged by address

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Memory TerminologyRandom Access Memory (RAM): Memory

in which individual cells can be easily accessed in any order

Dynamic Memory (DRAM): RAM composed of volatile memory

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Measuring Memory CapacityKilobyte: 210 bytes = 1024 bytes

Example: 3 KB = 3 times1024 bytesSometimes “kibi” rather than “kilo”

Megabyte: 220 bytes = 1,048,576 bytesExample: 3 MB = 3 times 1,048,576 bytesSometimes “megi” rather than “mega”

Gigabyte: 230 bytes = 1,073,741,824 bytesExample: 3 GB = 3 times 1,073,741,824 bytesSometimes “gigi” rather than “giga”

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Mass StorageOn-line versus off-lineTypically larger than main memoryTypically less volatile than main memoryTypically slower than main memory

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Mass Storage SystemsMagnetic Systems

DiskTape

Optical SystemsCDDVD

Flash Drives

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Figure 1.9 A magnetic disk storage system

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Figure 1.10 Magnetic tape storage

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Figure 1.11 CD storage

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FilesFile: A unit of data stored in mass storage

systemFields and keyfields

Physical record versus Logical recordBuffer: A memory area used for the

temporary storage of data (usually as a step in transferring the data)

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Figure 1.12 Logical records versus physical records on a disk

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Representing TextEach character (letter, punctuation,

etc.) is assigned a unique bit pattern.ASCII: Uses patterns of 7-bits to represent

most symbols used in written English textUnicode: Uses patterns of 16-bits to represent

the major symbols used in languages world side

ISO standard: Uses patterns of 32-bits to represent most symbols used in languages world wide

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Figure 1.13 The message “Hello.” in ASCII

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Representing Numeric ValuesBinary notation: Uses bits to represent a

number in base twoLimitations of computer representations of

numeric valuesOverflow – occurs when a value is too big to be

representedTruncation(截断 ) – occurs when a value cannot

be represented accurately

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Representing ImagesBit map techniques

Pixel: short for “picture element”RGBLuminance and chrominance

Vector techniquesScalableTrueType and PostScript

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Representing SoundSampling techniques

Used for high quality recordingsRecords actual audio

MIDIUsed in music synthesizersRecords “musical score”

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Figure 1.14 The sound wave represented by the sequence 0, 1.5, 2.0, 1.5, 2.0, 3.0, 4.0, 3.0, 0

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The Binary SystemThe traditional decimal system is based on powers of ten.

The Binary system is based on powers of two.

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Figure 1.15 The base ten and binary systems

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Figure 1.16 Decoding the binary representation 100101

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Figure 1.17 An algorithm for finding the binary representation of a positive integer

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Figure 1.18 Applying the algorithm in Figure 1.15 to obtain the binary representation of thirteen

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Figure 1.19 The binary addition facts

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Figure 1.20 Decoding the binary representation 101.101

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Storing IntegersTwo’s complement notation: The most

popular means of representing integer valuesExcess notation: Another means of

representing integer valuesBoth can suffer from overflow errors.

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Figure 1.21 Two’s complement notation systems

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Figure 1.22 Coding the value -6 in two’s complement notation using four bits

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Figure 1.23 Addition problems converted to two’s complement notation

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Figure 1.24 An excess eight conversion table

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Storing FractionsFloating-point Notation: Consists of a sign

bit, a mantissa field, and an exponent field.Related topics include

Normalized formTruncation errors

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Figure 1.26 Floating-point notation components

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Data CompressionLossy versus losslessRun-length encodingFrequency-dependent encoding

(Huffman codes)Relative encodingDictionary encoding (Includes adaptive

dictionary encoding such as LZW encoding.)

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Compressing ImagesGIF: Good for cartoonsJPEG: Good for photographsTIFF: Good for image archiving

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Compressing Audio and VideoMPEG

High definition television broadcastVideo conferencing

MP3Temporal maskingFrequency masking

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Communication ErrorsParity bits (even versus odd)CheckbytesError correcting codes

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Figure 1.28 The ASCII codes for the letters A and F adjusted for odd parity

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Figure 1.29 An error-correcting code

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