Lecture 1: Foundations of Computer Circuitry, Information Theory, and Signal Processing

Goals and Objectives of Studying Computer Circuitry and Architecture

Circuitry and computer architecture is a scientific and technical discipline dedicated to the study of theoretical methods for the analysis and synthesis of computer (electronic computing machine) circuits and the means of their technical implementation. The development of computer circuitry serves as the fundamental basis for improving computer architecture, qualitatively increasing productivity and reliability, and significantly reducing weight and dimensions. Computers are widely used across various sectors of the economy.

The primary goal of studying this discipline is to master the architecture, characteristics, and functioning principles of all functional devices within modern computers. The scope covers the current state and future prospects of computing technology; the structure, organization, and characteristics of computing complexes; storage devices; peripheral equipment; and interfaces. Furthermore, it encompasses system engineering and functioning principles of major computer types, computing complexes, and microprocessor systems, as well as the technological foundations for creating and operating technical means of information technology.

Students are expected to acquire the ability to apply theoretical knowledge and practical skills in using integrated circuits (ICs) to implement basic nodes from sets of logical and analog elements. This includes synthesizing combinational circuits and digital automata of varying complexity during design and maintenance. Students are also introduced to the technological foundations of microelectronics, promising directions in circuitry, the implementation of computer elements through microchips, and the logical and operational foundations for constructing medium and large-scale integrated circuits (MSI and LSI), alongside the circuitry of memory storage devices.

Information Foundations of Computer Circuitry

The broad application of computers facilitates the scientific and technical development of a nation, covering nearly all areas of human activity. A computer is defined as a program-controlled physical system intended for the algorithmic processing of information represented by signals. In a broad sense, information is a reflection of the real world. It is a unique, non-diminishing resource for life support; notably, its volume currently doubles every year. Information that has been prepared specifically for processing on computers is referred to as data.

The information process consists of several distinct stages where computer circuitry tools are applied. These stages include the collection of information from various sources and its representation in a form required for computer input; the transmission or forwarding of information from a source to a receiver; storage, which is the process of transmitting information through time; processing, involving the systematic execution of operations on data; and providing the processing results to the user.

Information must meet specific requirements to be effective: correctness (unambiguity of perception), value (utility), promptness (relevance or timeliness), accuracy, reliability, and stability (the ability to react to changes in initial data). Additionally, information must possess sufficiency or completeness, meaning the presence of the minimum necessary volume of information required to make a correct decision.

Informatics and Information Theory

Informatics studies the structure and general properties of information processes. It encompasses information theory; algorithmic, software, and hardware computer tools for information processing; and computer architecture, artificial intelligence systems, and computing networks. Information theory specifically investigates processes of transmission, transformation, and storage.

Within information theory, several areas are emphasized: methods for determining the amount of information in a message; rational means of representing information using various symbols such as letters and digits; and tools for the formation, detection, and evaluation of information process parameters. A message is defined as an ordered sequence of symbols (letters, digits, mathematical signs) intended for information transmission and encoded in a material form.

An information message is always linked to a source and a receiver, which are connected by a transmission channel. Both humans and technical devices, such as computers, sensors, and indicators, can act as sources or receivers. A communication channel is a set of devices with one input and one output designed to transmit information over distances. Messages can take diverse forms, such as sound, text, images, or electrical voltage from sensors like thermocouples.

Information Carriers and Storage

Information messages are stored on machine carriers. An information carrier is any storage material environment intended for recording and storing information for the purpose of direct input into a computer. The carrier serves as an intermediate link between the computer and the primary document containing numerical data, text, diagrams, graphs, or measurements. Storage typically involves three operations: recording, actual storage, and reading. Information is recorded by changing the physical or mechanical properties of the storage medium, and data is read by converting it back into electrical signals. Signals are stored in the carrier in a coded form.

Carriers are classified by various criteria. By accumulation medium, they are divided into continuous (magnetic tapes and disks) and discrete, where each unit of data is allocated a specific discrete area or element (ferrite cores, punch cards, punched tapes, triggers, cryotrons). By material type, they include paper (with text or drawings), paper punched tapes/cards, magnetic films, magnetic tapes/disks, and semiconductor memory circuits. Reading methods include mechanical, optical, magnetic, and electrical. Constructive designs range from tape and disk to electronic formats.

Nature and Classification of Signals

For information to be transmitted from a source to a receiver, messages are converted into signals. According to DSTU 2938-94, a signal is the change of a physical quantity used for transferring data. It is formed based on a physical quantity, known as the energy carrier (such as electromagnetic oscillations or electrical voltage), by changing one or more parameters (amplitude, frequency, phase, duration) according to the law of the transmitted information. A signal is the material-energy embodiment of a message. Signals can be transformed from one physical quantity to another more convenient for transmission without changing the meaning of the information.

Modulation is the process of changing physical parameters according to the law of the transmitted message, and these changed parameters are called informative parameters. Signals are classified by several features: degree of certainty (random and deterministic); time change structure (continuous and discrete); role in the computer (addresses, data, and control); spectral representation (low-frequency and high-frequency, narrowband and wideband); transformation method (coded, decoded, amplified, sampled); and connection type (telegraph, telephone, radar, inter-machine, and intra-machine). They are also classified by the character of change in coded signals at synchronized moments, such as potential (level-based) and impulse signals.

Information exchange uses signs of different ranks. The first rank consists of symbols, which are elementary units of a message. A limited set of symbols is called an alphabet, such as the Latin alphabet or binary symbols 0 and 1. The second rank consists of words (groups of symbols) from which phrases and expressions are constructed. Generally, the formalized description of signals and messages is called information representation.

Mathematical Representation and the Sampling Theorem

Information theory focuses on the mathematical representation of signals using functions, formulas, graphs, and probability distribution laws. The most common representation methods are temporal, spectral, and statistical. When information from physical processes arrives via sensors, it often appears as electrical signals changing continuously over time. There are four varieties of signals described by a time function $y(t)$.

The first variety is a continuous function of a continuous argument within a time interval $0 \le t \le t_k$ (analog signal). The second is a discrete function of a continuous argument, where values $y_i$ form a discrete series ($i = 1, 2, ..., k$), but the argument can be any value in the interval. Converting a continuous function into a discrete set of values is called level quantization. The third is a continuous function of a discrete argument, where function values are determined only at discrete moments $t_i$; this conversion is known as sampling or time quantization. The fourth is a discrete function of a discrete argument, where both function and argument take discrete values ($y_0, y_1, ..., y_k$ and $t_0, t_1, ..., t_k$).

According to the Kotelnikov theorem (sampling theorem), a signal described by a function with a limited spectrum is completely determined by its discrete values sampled at time intervals of $\Delta t = \frac{1}{2F_c}$, where $F_c$ is the width of the spectrum. This allows a computer to fully reconstruct the original continuous signal from these finite instantaneous values.

Digital Coding and Transmission Modes

Computer circuitry utilizes bit-digital (or simply digital) coding, where the primary signal is represented by a group of symbols reflecting binary digits 0 and 1 as electrical signals, such as pulses. The presence of a pulse corresponds to the digit 1, while its absence corresponds to 0. Digital codes can be transmitted in two primary ways: serial and parallel.

In serial coding, the digital code is transmitted sequentially over time using a single transmission channel. Each bit is sent one after another over a clock period $T_c$. Parallel coding involves simultaneous multi-channel transmission, where multiple bits (e.g., $x_0, x_1, x_2, x_3$) are sent across separate lines at the same time. In practice, serial codes are used for long-distance transmissions, such as between computers, while parallel codes are used for short distances, such as intra-machine communication.