Improved Teaching Pedagogy for Convolution of Continuous Time Signals

2019 ◽  
Author(s):  
Ikram E Khuda ◽  
Haider Abbas Naqvi ◽  
Ali Ahmed Siddiqui
Keyword(s):  
Continuous Time ◽  
Teaching Pedagogy ◽  
Time Signals

Continuous-time Signals

2015 ◽  
pp. 65-122
Author(s):  
Luis Chaparro
Keyword(s):  
Continuous Time ◽  
Time Signals

Deterministic Continuous-Time Signals and Systems

2021 ◽  
pp. 562-598
Author(s):  
Stevan Berber
Keyword(s):  
Discrete Time ◽  
Continuous Time ◽  
Linear Time ◽  
Continuous Variable ◽  
Linear Time Invariant ◽  
Time Signals ◽  
Analysis And Synthesis ◽  
Linear Time Invariant Systems ◽  
Definition Of ◽  
Time Invariant

Due to the importance of the concept of independent variable modification, the definition of linear-time-invariant system, and their implications for discrete-time signal processing, Chapter 11 presents basic deterministic continuous-time signals and systems. These signals, expressed in the form of functions and functionals such as the Dirac delta function, are used throughout the book for deterministic and stochastic signal analysis, in both the continuous-time and the discrete-time domains. The definition of the autocorrelation function, and an explanation of the convolution procedure in linear-time-invariant systems, are presented in detail, due to their importance in communication systems analysis and synthesis. A linear modification of the independent continuous variable is presented for specific cases, like time shift, time reversal, and time and amplitude scaling.

Digital Filters

2011 ◽  
pp. 180-196
Author(s):  
Gordana Jovanovic-Dolecek
Keyword(s):  
Discrete Time ◽  
Continuous Time ◽  
Digital Filters ◽  
Time Signal ◽  
Digital Signals ◽  
Video Signals ◽  
Time Signals ◽  
Time Distance ◽  
Independent Variable ◽  
Distance Position

A signal is defined as any physical quantity that varies with changes of one or more independent variables, and each can be any physical value, such as time, distance, position, temperature, or pressure (Oppenheim & Schafer, 1999; Elali, 2003; Smith, 2002). The independent variable is usually referred to as “time”. Examples of signals that we frequently encounter are speech, music, picture, and video signals. If the independent variable is continuous, the signal is called continuous-time signal or analog signal, and is mathematically denoted as x(t). For discrete-time signals the independent variable is a discrete variable and therefore a discrete-time signal is defined as a function of an independent variable n, where n is an integer. Consequently, x(n) represents a sequence of values, some of which can be zeros, for each value of integer n. The discrete–time signal is not defined at instants between integers and is incorrect to say that x(n) is zero at times between integers. The amplitude of both the continuous and discrete-time signals may be continuous or discrete. Digital signals are discrete-time signals for which the amplitude is discrete. Figure 1 illustrates the analog and the discrete-time signals.

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