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Stack #4633289
| Question | Answer |
|---|---|
| Definition: Signal | A signal is a measurable physical quantity used to transmit information |
| Definition: System | A physical device that performs one or more operations on a signal |
| Definition: Signal Processing | A process where by useful information is extracted from a signal |
| Question: Examples of real world signal processing include: | EEGs - recording brain activity on the scalp, Speech Processing, Seismograms - records of ground motion from geological and environmental phenomena, Time series analysis - like stock market prediction |
| Definition: Information | The useful part of a signal |
| Definition: Noise | Any part of a signal that is not information |
| Definition: Information-to-noise ratio | The amount of the signal that is useful as information to us versus the amount of non useful noise information as a ratio |
| Question:Will signals always have noise, why or why not? | Yes, because of the nature of signal propagation in the real world |
| Question: Real world signals are usually (analog/discrete) and why? | Analog, because the real world is analog |
| Definition: Analog Signal (included how they are processed) | A signal that always has continuous variation in time and amplitude, that are processed directly and continuously |
| Question: What is a useful way of knowing if something is analog? | Ask yourself whether it has a value for every infinitesimally small moment in time |
| Question: Can analog signals be processed by a clocked electronic, why or why not? | No because clocking is inherently discrete, using discrete intervals of time. Thus a continuous analog signal cannot be accurately described by a clocked one. |
| Question: Are analog signals computationally efficient, yes or no and why? | Yes, because it must occur in a real time, so there cannot be too much complexity. |
| Question: What are analog to digital converters (ADC) and digital to analog converters(DAC) | ADC converts analog signals to digital ones, and DAC converts digital signals to analog. |
| Question: What are the three steps involved in analog to digital conversion? | 1. Sampling the analog signal at discrete steps 2. Quantizing the measured signal at each time step into discrete levels 3. Encoding these levels into a binary number. |
| Question: In sampling, will there be information loss? | Yes because you are inherently not taking the whole signal. We sample at intervals |
| Definition: Sampling | Retaining a signal only at particular instances in time. We sample at a constant time interval (Δt) |
| Question: When is sampling and quantizing useful? | When we want to store a signal of finite duration in finite-sized memory space |
| Definition: Quantizing | Binning/rounding a signal amplitude to a discrete set of values( ΔY) |
| Definition: Digitizing | Sampling and quantizing a signal so it becomes discrete amplitudes at discrete time intervals. |
| Question: Mathematically what does a quantized, sampled, and digital signal look like | Quantized signals look like so y(t)ΔY, so that it is the original signal at discrete amplitudes Sampled signals look like y(nΔt) so that it is the orignal signal at discrete time intervals Digitized Signals look like y(nΔt)ΔY, because its combo |
| Definition: Encoding | Mapping quantized signal amplitudes to binary numbers so that the signal can be stored in a computer system |
| Question: How are sampling interval and quantization interval linked? | Inversely: Smaller sampling interval means bigger quantization interval and vice versa. |
| Question: What are the advantages of a digital signal compared to an analog one? | Bits of the signal are either 0 or 1, so it is robust against small fluctuations Can be implemented/debugged in software Easy to store and transmit Can be parallelized and/or shared Independent of external parameters (vibrations, temperature, power) |
| Question: What are the disadvantages of digital signals compared to analog ones? | Often very complex to digitize Limited frequency range, depending on sampling interval Consumes electrical power Not real time Limited in speed by clocking |
| Question: What are the 5 main ways of classifying a signal? | 1. Is the signal continuous valued or discrete valued 2. Is the signal continuous time or discrete time 3. Is the signal single-channel or multi-channeled 4. Is the signal single dimension or multi-dimension 5. Is the signal deterministic or random? |
| Definition: Continuous time signals are | Signals that have a time for any measurable value, defined on continuous domains, represented by continuous functions (e.g. f(t)), and are operated on by differentiation/integration |
| Definition: Discrete time signals are | Signals that are only defined at pre-defined instances of time, defined on a set, represented by integer indexes, and operated on by first principles or summations |
| Definition: Continuous valued signals are: | Signals that have an amplitude value for all of a range, defined on a continuous range, represented as a real or complex number, and processed signals take on the value based on math operations used. |
| Definition: Discrete valued signals are: | Signals that are only defined on certain predefined amplitudes, defined on a set of integer numbers, represented with a scaling constant multiplied by the integer index, and the processed signals must be rounded, binned or truncated to discrete levels |
| Definition: Single channelled signals are: | Signals that are usually generated from one source, represented by a scalar function or column matrix |
| Definition: Multi channelled signals are: | Signals usually generated from multiple sources, represented by vector valued functions or a series of arrays |
| Definition: One dimensional signals are: | Signals represented by a scalar function of one independent variable, usually time, like time series or other series |
| Definition: Multi-dimensional signals are: | Signals represented by a scalar function of N independent variables, or an array of numbers |
| Definition: Deterministic signals are: | Signals who's 'future' can be uniquely and accurately described by mathematics based on precise knowledge on the 'past' |
| Definition: Random signals are: | Signals who are never known prior to measurement and you cannot predict where they want to go |
| Question: In real life is there really a boundary between deterministic and random signals | No, because a deterministic signal is only that until it stops being that, and the universe is random, but we know that we are trending to a state of lower energy (entropy). Everything is always random |
| Question: Do deterministic signals carry much meaningful information? | Often no, because we wont learn anything new that we couldnt have calculated, but noise is sometimes deterministic, so we can do with that what we want |
Created by:
EngineeringGirl