chapter 1: data storage
DESCRIPTION
Chapter 1: Data Storage. Chapter 1: Data Storage. 1.1 Bits and Their Storage 1.2 Main Memory 1.3 Mass Storage 1.4 Representing Information as Bit Patterns 1.5 The Binary System. Chapter 1: Data Storage (continued). 1.6 Storing Integers 1.7 Storing Fractions 1.8 Data Compression - PowerPoint PPT PresentationTRANSCRIPT
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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