Name: signal transformations in time and amplitude
Uploaded: 2024-09-26T13:16:54.000Z
Duration: 1 min 22 s
Channel: JoVE

기본 신호 연산은 시간 반전, 스케일링, 이동 및 진폭 변환입니다.
시간 반전은 시간이 0일 때 세로축에 대한 연속시간 신호를 미러링하며, 't'를 음의 't'로 대체하여 달성됩니다. 고려된 신호의 경우 결과가 그래픽으로 표시됩니다.
시간 스케일링은 't'를 'at'으로 바꿔 시간상 신호를 압축하거나 확장하며, 여기서 'a'는 상수입니다. 이 상수의 크기가 1보다 크면 신호가 압축됩니다. 1보다 작으면 확장됩니다.
이 상수의 음수 값은 시간 반전과 압축 또는 확장을 모두 유도합니다. 이것은 고려된 신호를 사용하여 그래픽으로 표현할 수 있습니다.
연속 시간 신호의 시간 이동은 't 0'이 일정한 't − t0'으로 대체하여 수행됩니다. 양수 상수는 신호를 원점에서 오른쪽으로 지연시키고 이동하는 반면, 음수 상수는 신호를 전진시키고 왼쪽으로 이동합니다.
연속시간 신호의 진폭 변환은 'A'와 'B'가 상수인 일반적인 형식을 취합니다. 그래프는 예시된 신호의 진폭 변환을 보여줍니다.

신호에 대한 기본 연산

Basic Operations on Signals

기본 신호 연산에는 시간 역전, 시간 스케일링, 시간 이동 및 진폭 변환이 포함됩니다. 이러한 연산은 신호 처리 및 분석에서 기본이 됩니다.

시간 역전은 수직 축에 대해 t=0에서 연속 시간 신호를 미러링합니다. 이는 t를 −t로 대체하여 달성됩니다. 예를 들어, 신호 x(t)가 고려되는 경우 시간 역전 신호는 x(−t)입니다. 이 연산은 미러링된 신호를 보여주는 그래픽으로 표현할 수 있습니다.

<img alt="Figure1" src="/files/ftp_upload/16044/16044_PT%20Figure_1.svg" style="height: 150px;">

시간 스케일링은 t를 at로 대체하여 시간적으로 신호를 압축하거나 확장합니다. 여기서 a는 상수입니다. ∣a∣&gt;1이면 신호가 압축됩니다. ∣a∣&lt;1이면 확장됩니다. a의 음수 값은 시간 반전과 압축 또는 확장을 모두 유도합니다. 신호에 대한 이 연산의 그래픽 표현은 이러한 효과를 보여줍니다.

연속 시간 신호의 시간 이동은 t를 t−t_0으로 대체하여 수행됩니다. 여기서 t_0은 상수입니다. 양의 t_0은 신호를 지연시키고 오른쪽으로 이동시키는 반면, 음의 t_0은 신호를 진행하고 왼쪽으로 이동합니다. 예를 들어, t_0만큼 이동된 신호 x(t)는 x(t−t_0)으로 표현됩니다.

연속 시간 신호의 진폭 변환은 일반적으로 Ax(t)+B 형태이며, 여기서 A과 B는 상수입니다. 이러한 변환은 진폭을 확장하고 수직으로 이동할 수도 있습니다. 그래픽적으로 신호의 진폭 변환은 A만큼 확장하고 B만큼 이동하는 효과를 보여줍니다.

이러한 기본 작업(시간 반전, 스케일링, 이동 및 진폭 변환)은 신호를 조작하고 분석하는 데 필수적인 도구로, 신호 처리 애플리케이션에서 다양한 조정 및 수정을 허용합니다.

기본 신호 연산은 시간 반전, 스케일링, 이동 및 진폭 변환입니다.
시간 반전은 에 대한 연속 시간 신호를 반영합니다.

Education

교육

JoVE Core

Electrical Engineering

전기공학

Unit 1

제1단원

Introduction to Signals and Systems

신호 및 시스템 입문

KEY TERMS AND CONCEPTS

주요 용어 및 개념

signal transformations in time and amplitude

Signal transformations in time and amplitude are key tools in signal processing. They include time reversal, time scaling, time shifting, and amplitude changes. These operations help students describe how a continuous-time signal changes when it is mirrored, stretched, moved, or resized.

Time reversal flips a continuous-time signal about the vertical axis at t = 0. It is done by replacing t with -t, so x(t) becomes x(-t). A graph of the signal shows this mirrored shape clearly.

Time scaling changes how fast or slow a signal appears in time by replacing t with at, where a is a constant. If |a| &gt; 1, the signal compresses. If |a| &lt; 1, the signal expands. A negative value of a causes time reversal as well as compression or expansion.

Time shifting moves a continuous-time signal left or right by replacing t with t - t0, where t0 is a constant. A positive t0 delays the signal and shifts it to the right. A negative t0 advances the signal and shifts it to the left. Amplitude transformations use the form Ax(t) + B, where A and B are constants. These changes scale the signal’s height and can shift it up or down vertically.

Signal Transformations in Time and Amplitude

signal-transformations-in-time-and-amplitude

signal and system

Signals and Systems in Everyday Data

Signals and systems help describe how data moves through the world. A signal x(t) is a set of data or a time function that represents a variable of interest. It can carry information about atmospheric temperature, humidity, human voice, television images, a dog’s bark, or birdsongs. A signal can also depend on more than one independent variable. An image, for example, depends on horizontal and vertical position, so it can be treated as a two-dimensional signal. In this course, the focus is on...

classification of signals

Signal Types by Time and Amplitude

Signals in signal processing are grouped by time behavior, amplitude, and whether they start before or after time zero. These signal classes help students describe and compare signals before they are analyzed or processed. A continuous-time signal has a value at every instant in time. A discrete-time signal has values only at specific moments, often written as x(n), where n is an integer. Discrete-time signals often come from systems with naturally discrete values, such as digital audio...

energy and power signals

Power and Energy in Electrical Signals

Power and energy in electrical signals are measured from voltage and current across a resistor. These signals help describe how much energy a signal carries and how much power it delivers over time. For a continuous-time signal, total energy is found by integrating the square of the signal's magnitude over a chosen time interval. Time-averaged power is then the total energy divided by the length of that interval. For a discrete-time signal, total energy is found by summing the squares of the...

even and odd signals

Signal Symmetry and Decomposition

Signal symmetry helps classify continuous-time and discrete-time signals as even or odd. An even signal matches its time-reversed version. It mirrors around the vertical axis, so the values at negative time match the values at positive time. An odd signal does not match its time-reversed counterpart. It has antisymmetry about the vertical axis. These symmetry rules are used in both continuous-time and discrete-time signal analysis. Any continuous-time signal can be split into even and odd...

basic continuous time signals

Step, Impulse, and Ramp Signals

Step, impulse, and ramp signals are the main basic continuous-time signals. They are also called singularity functions. These signals are known for discontinuities or for derivatives that are discontinuous. The unit step function, written as u(t), is zero for negative time values and one for positive time values. It has a jump at t = 0. In many cases, it can model an abrupt change, such as the step voltage that appears when a car ignition key is turned. The derivative of the unit step...

rectangular and triangular pulse function

rectangular-and-triangular-pulse-function

Modeling Pulses with Rectangles and Triangles

Rectangular and triangular pulse functions are basic signal shapes used to model waveforms in signal processing. The rectangular pulse has a flat top and is centered at the origin with a height of one unit. It is described by two parameters: T, which gives the center location on the time axis, and τ, which sets the pulse duration. A rectangular pulse can also represent a real signal with a chosen amplitude and length. For example, a pulse with a 5 V amplitude, a 3-second duration, and a center...

exponential and sinusoidal signals

Complex Exponentials in Signal Behavior

Exponential and sinusoidal signals are used to describe how waveforms change over time. The continuous-time exponential function uses constants α and A. When both are real, it shows exponential growth or decay. Graphs of these signals make the rise or drop easy to see. When α is purely imaginary, the signal becomes a complex exponential. In this form, j is the imaginary unit and ω0 is the angular frequency. A complex exponential is periodic when its magnitude is unity. That periodic behavior...

basic discrete time signals

Discrete-Time Signal Basics and Shapes

Discrete-time signals include several basic sequences used in signal processing. The unit step sequence is 1 for zero and positive values of the integer n. A graph of eight sample points shows it as a step that begins at n = 0 and stays constant after that. The unit impulse, also called the sample sequence, is 0 for every n except at n = 0, where it equals 1. This sequence is written as δ(n). It is the first difference of the unit step sequence, and the unit step sequence u(n) is the...

basic operations on signals

Signal transformations in time and amplitude are key tools in signal processing. They include time reversal, time scaling, time shifting, and amplitude changes. These operations help students describe how a continuous-time signal changes when it is mirrored, stretched, moved, or resized. Time reversal flips a continuous-time signal about the vertical axis at t = 0. It is done by replacing t with -t, so x(t) becomes x(-t). A graph of the signal shows this mirrored shape clearly. Time scaling...

classification of systems-i

System Properties: Linearity, Causality, Memory

System properties such as linearity, causality, and memory help describe how a system responds to input. These ideas are useful for studying and designing systems in engineering. A system can be checked by looking at how its output changes with different inputs. Linearity means the input-output relationship follows homogeneity and additivity. Homogeneity says that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Additivity means the response...

classification of systems-ii

Continuous and Discrete System Models

Continuous-time and discrete-time systems are two common ways to model signals and their outputs. In continuous-time systems, both input and output signals change smoothly as time moves continuously. These systems are often written with differential or algebraic equations. An RC circuit is one example of a continuous-time system. Its input and output voltage can be related by a differential equation based on Ohm’s law and the capacitor relation. Discrete-time systems work differently. Their...

key terms and concepts

Learn how time reversal, time scaling, time shifting, and amplitude transformations change continuous-time signals in signal processing and graph form.

Signal Transformations in Time and Amplitude | JoVE K12

JoVE Core Electrical Engineering offers easy-to-understand animated videos that cover fundamental concepts of electric circuits along with circuit analysis techniques. It incorporates first-order and second-order circuits using operational amplifiers and circuit transformation concepts. The inclusion of practical design examples and real-world applications through scientist-in-action videos adds significant educational value, making complex concepts accessible.

electrical engineering

Signal Transformations in Time and Amplitude

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