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3 years ago

Find the value of x acellus help please

Mathematics

2 answers:

ipn [44]3 years ago

7 0

Answer:

Step-by-step explanation:

By Basic Proportionality Theorem:

$\frac{4}{10} = \frac{x}{25} \\ \\ x = \frac{4 \times 25}{10} \\ \\ x = \frac{100}{10} \\ \\ x = 10$

balu736 [363]3 years ago

5 0

Answer:

Step-by-step explanation:

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Answer:

IM and YM

Step-by-step explanation:

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What are the coordinates of the vertex of the parabola with the equation y=x^2+2x-3

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A sporting good store sells tennis balls in boxes. Each box has 4 sleeves of tennis balls. Each sleeve has 3 tennis balls. The s

Afina-wow [57]

Answer:

The total number of tennis ball did store sell in all is 1,356

Step-by-step explanation:

Given as :

The number of sleeves of tennis ball in each box = 4

The number of tennis ball in each sleeve = 3

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The selling of boxes on Saturday = 67

The selling of boxes on Sunday = 46

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3 years ago

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C/5 when c=10 so 10/5 but wouldn’t that be 2

aalyn [17]

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3 years ago

An analogue sensor signal is sampled every 0.4ms to convert it into a digital representation. What is the corresponding sampling

kondaur [170]

<h2>Hello! It will be a pleasure to help you! </h2><h2>So let's get started:</h2><h3 /><h2>PART 1. </h2><h3>An analogue sensor signal is sampled every 0.4ms to convert it into a digital representation. What is the corresponding sampling rate?</h3>

Sampling is simply a reduction of a continuous time signal to a discrete time signal. Here we know that an analogue sensor is sampled every $0.4ms$ to convert it into a digital representation. So sampling rate, also called the sampling frequency or $f_{s}$ , is the average number of samples obtained in one second, that is, samples per second:

$f_{s}=\frac{1}{T}$

Since we know:

$T=0.4ms$

Then, the sampling rate is:

$f_{s}=\frac{1}{0.4ms} \\ \\ f_{s}=2,500 \ samples \ per \ second \\ \\ Or: \\ \\ \boxed{f_{s}=2.5kS/s}$

<h3 /><h2>PART 2. </h2><h3>According to the Sampling Theorem, for this sampling rate value, what will be the highest frequency in the digital representation, assuming the lowest frequency in the sensor signal is very close to zero.</h3><h3 />

Sampling Theorem (Nyquist Theorem) States:

<em>A </em><em>continuous time signal </em><em>can be completely represented in its samples and recovered back, if the sampling frequency </em> $f_{s}$ <em>is greater than or equal to twice frequency component of the message signal.</em>

In other words:

$f_{s}\geq 2f_{m}$

So, the highest frequency in the digital representation will be:

$f_{m}=\frac{2500}{2} \\ \\ \boxed{f_{m}=1.25kHz}$

<h2>PART 3. </h2><h3>If each sample is quantised into 2048 levels, what will be the resulting bit-rate, giving your answer in scientific notation to 2 decimal places?</h3>

Everything is Ok up to this point! But let me explain something. We do all these things in order to get a faithful reproduction of the digital signal. So the Analog-to-Digital Conversion (ADC) allows us to do that.

In this final part, each sample is quantised to 2048 levels, so this number can be written as:

$2048=2^{11}$