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IT Theory IEB REAL COMPLETE 25 PAGES IN-DEPTH STUDY GUIDE CORRECTLY DETAILED.

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IT Theory IEB REAL COMPLETE 25 PAGES IN-DEPTH STUDY GUIDE CORRECTLY DETAILED. IT Theory IEB STUDY GUIDE Unit 1: Data Representation and Boolean Logic Data Representation Fundamentals • Word Size: A word is defined as the number of bits the CPU can process simultaneously. Common sizes include 32-bit (4 bytes) and 64-bit (8 bytes), which directly influence the amount of data handled and processing speed. • Possible Combinations of Bits: Each bit can be either 0 or 1, leading to a total of 2ⁿ combinations for n bits. For example, with 4 bits, there are 16 combinations (2⁴ = 16).

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IT Theory IEB REAL COMPLETE 25 PAGES IN-DEPTH STUDY
GUIDE CORRECTLY DETAILED.
IT Theory IEB STUDY GUIDE
Unit 1: Data Representation and Boolean Logic
Data Representation Fundamentals
• Word Size: A word is defined as the number of bits the CPU can process
simultaneously. Common sizes include 32-bit (4 bytes) and 64-bit (8 bytes),
which directly influence the amount of data handled and processing speed.
• Possible Combinations of Bits: Each bit can be either 0 or 1, leading to a total of
2ⁿ combinations for n bits. For example, with 4 bits, there are 16 combinations
(2⁴ = 16).
• Binary Addition: The rules for binary addition include: 0 + 0 = 0, 0 + 1 = 1, 1 + 0 = 1,
and 1 + 1 = 10 (which carries over). This forms the basis for arithmetic
operations in binary systems.
• Representing Integers: Positive integers use standard binary, while negative
integers can be represented using Sign and Magnitude or Two's Complement
methods, the latter allowing for easier arithmetic operations.
• Integer Limits: Unsigned integers range from 0 to (2ⁿ - 1), while signed integers
(using Two's Complement) range from -2ⁿ⁻¹ to 2ⁿ⁻¹ - 1. For example, an 8-bit
unsigned integer ranges from 0 to 255, while a signed integer ranges from -128
to 127.
• Overflow and Underflow: Overflow occurs when calculations exceed the
maximum representable value, while underflow occurs when results fall below
the minimum. In unsigned integers, overflow wraps to 0, while signed integers
may yield incorrect signs.
Advanced Data Representation Techniques

, • Floating-Point Representation: Real numbers are represented using floating-
point notation, which includes a sign bit, mantissa (significant digits), and
exponent (scale). This allows for a wide range of values, accommodating both
very small and very large numbers.
• Errors in Data Representation: Rounding errors arise from approximating
numbers due to limited precision, while truncation errors occur when digits
are cut off. Both can accumulate and affect overall accuracy in calculations.
• Compression Techniques: Techniques such as using hexadecimal (base-16) for
compact representation of binary data are common. For instance, 1 hex digit
represents 4 binary digits. IPv4 uses 32-bit addresses, while IPv6 uses 128-bit
addresses, enhancing address space.
• Screen Resolution and RGB: Screen resolution is measured in pixels (width x
height), e.g., 1920x1080. The RGB color model uses 8 bits per channel, allowing
for 256 intensity levels per color, resulting in over 16 million possible colors.
• Truth Tables: Truth tables display all possible outcomes of logical operations.
For example, with four variables (A, B, C, D), there are 16 possible
combinations. De Morgan's Laws help simplify logical expressions, such as NOT
(A AND B) = (NOT A) OR (NOT B).
• Logic Gates: Basic logic gates include AND, OR, NOT, NAND, NOR, XOR, and
XNOR, each performing specific logical operations essential for digital circuits.
Boolean Algebra and Expressions
• Boolean Expressions: These are mathematical expressions that utilize Boolean
algebra, such as A AND (B OR C). They form the foundation for digital logic
design and circuit implementation.
• De Morgan's Theorems: These theorems provide rules for transforming logical
expressions, which are crucial for simplifying complex circuits and
understanding logical relationships.

, • Applications of Boolean Logic: Boolean logic is applied in various fields,
including computer science, electrical engineering, and digital circuit design,
enabling the creation of complex systems from simple logical operations.
• Practical Examples: Real-world applications of Boolean expressions include
programming conditions, circuit design, and algorithm development,
showcasing their versatility and importance in technology.
• Truth Table Construction: Constructing truth tables involves listing all possible
input combinations and their corresponding outputs, which is essential for
verifying the correctness of logical expressions and circuits.
• Complex Logic Circuits: Understanding how to combine multiple logic gates to
create complex circuits is fundamental in designing functional digital systems.
Unit 2: Hardware
Central Processing Unit (CPU) Design
content


o Definition: The CPU is the core component of a computer, responsible for
executing instructions and processing data. It is often referred to as the
'brain' of the computer.
• Components of the CPU: The CPU consists of several key components: Control
Unit (CU), which directs operations; Arithmetic Logic Unit (ALU), which
performs calculations; and Registers, which are small, fast storage locations
for temporary data.
• Machine Cycle: The CPU operates in a cycle consisting of four stages: Fetch
(retrieve instructions), Decode (interpret instructions), Execute (perform
operations), and Store (save results).
• Processing Techniques: Serial processing executes one instruction at a time,
while parallel processing allows multiple instructions to be processed

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