L2 SIGNALS Flashcards

1
Q

How to mathematically describe a signal: its amplitude, phase, frequency, period?

A

-Amplitude of a periodic variable is a measure of its change over a single period
-The frequency (in Hz) is defined as f = 1/T (T is period in secs) and it represents the number of patterns (cycles) contained in 1s
-(Period: the signal repeats its values every T seconds)

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2
Q

What is spatial resolution and color resolution in a sampled digital image?

A
  • Num of pixels that represent an image is called the spatial resolution of the image.
    -The number of bits necessary to represent the color or intensity is called the color or intensity resolution
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3
Q

What are the types of images (RGB, gray scale, black & white) and how are these types of images represented in a computer?

A

-The color resolution for a digital image in a RGB where each pixel has a color described by the amount of red, green and blue. This amount is encoded with 8 bits ranging from 0-255 The image is stored as vector of 3 arrays, one array for each R G B color. Since the number of bits required per pixel is 3x8, the image is called a 24-bit color image.

-For a black & white image AKA binary format, color resolution is only one bit. Each pixel is just black (1) or white (0).

-In a grayscale image, each pixel is a shade of gray, , normally from 0(black) to 255(white). Each pixel is represented by 8 bits hence color resolution is 8 bits

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4
Q

What is sampling?

A

Sampling periodically measures the signal’s level and produces a finite-length sequence of samples of infinite precision. We sample a continuous signal at equally spaced time instants Ts = sampling period. A discrete signal is represented by a sequence of samples s[n], where n is the integer index in the sequence
s[n] = s(nTs) with n = 0 … N – 1; N is the total number of samples

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5
Q

What is sampling freq?

A

The sampling frequency: fs = 1/Ts is the number of samples per second. Y
You have different kinds of sampling: image sampling, spatial sampling, color sampling.

  • Image sampling: a digital image is a result of sampling the real image formed by focusing on a camera lens
    o Sampling is done in space and in color
  • Spatial sampling: the 2D analog image formed by a camera is converted to a finite resolution digital image of individual pixels; brightness is sampled at a number of points
  • Color sampling: the analog brightness of the image is sampled at N*M pixels; see color resolution
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6
Q

What is sampling period?

A

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7
Q

What is an ADC, how does it work?

A

ADC means Analog-to-Digital-Converter. It is an electronic device that transforms an analog signal (for example an output voltage of a sensor) in a digital signal, that can be understood by computers.

What is an DAC, how does it work?
DAC means Digital-to-Analog-Converter. It is an electronic device that transforms a digital signal in an analog signal. This process is essential in order to extract the right information carried by the analog signal and to send commands to different actuators, such as motors, displays or loudspeakers.

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8
Q

What is an DAC, how does it work?

A

DAC means Digital-to-Analog-Converter. It is an electronic device that transforms a digital signal in an analog signal. This process is essential in order to extract the right information carried by the analog signal and to send commands to different actuators, such as motors, displays or loudspeakers.

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9
Q

WHAT is the Shannon theorem, what happens if we do not obey the Shannon theorem?
(answer: oversampling, underdamping => aliasing)

A

The Shannon sampling theorem says that the appropriate sampling frequency is double the size of the signal frequency. If we do not follow this rule, then we might have to deal with either oversampling, which is not that bad, as it creates a smoother reconstructed waveform, but oversampling, so a higher sampling frequency than the Shannon sampling theorem boosts up the storage and computational needs of the system. Another scenario is undersampling with a sampling frequency lower than the theorem rate, which is known as aliasing, where no difference is found between the low-frequency alias of the high-frequency signal.

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