# 5.4 Discrete-time signals and systems

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Mathematically, analog signals are functions having as their independent variables continuous quantities, such as space andtime. Discrete-time signals are functions defined on the integers; they are sequences. As with analog signals, we seekways of decomposing discrete-time signals into simpler components. Because this approach leads to a betterunderstanding of signal structure, we can exploit that structure to represent information (create ways of representinginformation with signals) and to extract information (retrieve the information thus represented). For symbolic-valued signals,the approach is different: We develop a common representation of all symbolic-valued signals so that we can embody theinformation they contain in a unified way. From an information representation perspective, the most important issue becomes,for both real-valued and symbolic-valued signals, efficiency: what is the most parsimonious and compact way to representinformation so that it can be extracted later.

## Real- and complex-valued signals

A discrete-time signal is represented symbolically as $s(n)$ , where $n=\{\dots , -1, 0, 1, \dots \}$ .

We usually draw discrete-time signals as stem plots to emphasize the fact they are functions defined only on theintegers. We can delay a discrete-time signal by an integer just as with analog ones. A signal delayed by $m$ samples has the expression $s(n-m)$ .

## Complex exponentials

The most important signal is, of course, the complex exponential sequence .

$s(n)=e^{i\times 2\pi fn}$
Note that the frequency variable $f$ is dimensionless and that adding an integer to the frequency of the discrete-time complex exponential has no effect on the signal's value.
$e^{i\times 2\pi (f+m)n}=e^{i\times 2\pi fn}e^{i\times 2\pi mn}=e^{i\times 2\pi fn}$
This derivation follows because the complex exponential evaluated at an integer multiple of $2\pi$ equals one. Thus, we need only consider frequency to have a value in some unit-length interval.

## Sinusoids

Discrete-time sinusoids have the obvious form $s(n)=A\cos (2\pi fn+\phi )$ . As opposed to analog complex exponentials and sinusoids that can have their frequencies be any real value,frequencies of their discrete-time counterparts yield unique waveforms only when $f$ lies in the interval $\left(-\left(\frac{1}{2}\right) , \frac{1}{2}\right]$ . This choice of frequency interval is arbitrary; we can also choose the frequency to lie in the interval $\left[0 , 1\right)$ . How to choose a unit-length interval for a sinusoid's frequency will become evident later.

## Unit sample

The second-most important discrete-time signal is the unit sample , which is defined to be

$\delta (n)=\begin{cases}1 & \text{if n=0}\\ 0 & \text{otherwise}\end{cases}$
Examination of a discrete-time signal's plot, like that of the cosine signal shown in [link] , reveals that all signals consist of a sequence of delayed andscaled unit samples. Because the value of a sequence at each integer $m$ is denoted by $s(m)$ and the unit sample delayed to occur at $m$ is written $\delta (n-m)$ , we can decompose any signal as a sum of unit samples delayed to the appropriate location andscaled by the signal value.
$s(n)=\sum_{m=()}$ s m δ n m
This kind of decomposition is unique to discrete-time signals, and will prove useful subsequently.

## Unit step

The unit step in discrete-time is well-defined at the origin, as opposed to the situation with analog signals.

$u(n)=\begin{cases}1 & \text{if n\ge 0}\\ 0 & \text{if n< 0}\end{cases}$

## Symbolic signals

An interesting aspect of discrete-time signals is that their values do not need to be real numbers. We do have real-valueddiscrete-time signals like the sinusoid, but we also have signals that denote the sequence of characters typed on thekeyboard. Such characters certainly aren't real numbers, and as a collection of possible signal values, they have littlemathematical structure other than that they are members of a set. More formally, each element of the symbolic-valued signal $s(n)$ takes on one of the values $\{{a}_{1}, \dots , {a}_{K}\}$ which comprise the alphabet $A$ . This technical terminology does not mean we restrict symbols to being members of the Englishor Greek alphabet. They could represent keyboard characters, bytes (8-bit quantities), integers that convey dailytemperature. Whether controlled by software or not, discrete-time systems are ultimately constructed from digitalcircuits, which consist entirely of analog circuit elements. Furthermore, the transmission andreception of discrete-time signals, like e-mail, is accomplished with analog signals and systems. Understandinghow discrete-time and analog signals and systems intertwine is perhaps the main goal of this course.

## Discrete-time systems

Discrete-time systems can act on discrete-time signals in ways similar to those found in analog signals and systems. Becauseof the role of software in discrete-time systems, many more different systems can be envisioned and "constructed" withprograms than can be with analog signals. In fact, a special class of analog signals can be converted into discrete-timesignals, processed with software, and converted back into an analog signal, all without the incursion of error. For suchsignals, systems can be easily produced in software, with equivalent analog realizations difficult, if not impossible,to design.

can someone help me with some logarithmic and exponential equations.
20/(×-6^2)
Salomon
okay, so you have 6 raised to the power of 2. what is that part of your answer
I don't understand what the A with approx sign and the boxed x mean
it think it's written 20/(X-6)^2 so it's 20 divided by X-6 squared
Salomon
I'm not sure why it wrote it the other way
Salomon
I got X =-6
Salomon
ok. so take the square root of both sides, now you have plus or minus the square root of 20= x-6
oops. ignore that.
so you not have an equal sign anywhere in the original equation?
Commplementary angles
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Sherica
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Sherica
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Tamia
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a perfect square v²+2v+_
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algebra 2 Inequalities:If equation 2 = 0 it is an open set?
or infinite solutions?
Kim
The answer is neither. The function, 2 = 0 cannot exist. Hence, the function is undefined.
Al
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Kristine 2*2*2=8
Differences Between Laspeyres and Paasche Indices
No. 7x -4y is simplified from 4x + (3y + 3x) -7y
is it 3×y ?
J, combine like terms 7x-4y
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Asali
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Need to simplify the expresin. 3/7 (x+y)-1/7 (x-1)=
. After 3 months on a diet, Lisa had lost 12% of her original weight. She lost 21 pounds. What was Lisa's original weight?
what's the easiest and fastest way to the synthesize AgNP?
China
Cied
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I start with an easy one. carbon nanotubes woven into a long filament like a string
Porter
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Porter
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Yasmin
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Cesar
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Yes, Nanotechnology has a very fast field of applications and their is always something new to do with it...
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Stotaw
In this morden time nanotechnology used in many field . 1-Electronics-manufacturad IC ,RAM,MRAM,solar panel etc 2-Helth and Medical-Nanomedicine,Drug Dilivery for cancer treatment etc 3- Atomobile -MEMS, Coating on car etc. and may other field for details you can check at Google
Azam
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Prasenjit
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Azam
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Damian
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At high concentrations (>0.01 M), the relation between absorptivity coefficient and absorbance is no longer linear. This is due to the electrostatic interactions between the quantum dots in close proximity. If the concentration of the solution is high, another effect that is seen is the scattering of light from the large number of quantum dots. This assumption only works at low concentrations of the analyte. Presence of stray light.
the Beer law works very well for dilute solutions but fails for very high concentrations. why?
how did you get the value of 2000N.What calculations are needed to arrive at it
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