Virtual Labs

Adaptive Filtering of Bio-signals Using LMS and RLS Algorithms

What does RLS stand for in the context of adaptive filtering?

a: Recursive Least Squares b: Recurrent Linear System c: Random Least Squares d: Recursive Linear Smoothing

What is the primary goal of the LMS, RLS algorithms in adaptive filtering?

a: To increase the complexity of the filter b: To minimize the computational load c: To minimize the error between the desired signal and the actual output d: To maximize the filter's order

In which applications is the RLS algorithm particularly advantageous due to its fast convergence properties?

a: Image processing b: Echo cancellation and noise reduction c: Data encryption d: Video streaming

What does LMS stand for in the context of adaptive filtering?

a: Least Mean Square Algorithm b: Least Median Square Algorithm c: Largest Mean Square Algorithm d: None of the above

Which of the following statements is true about the computational complexity of the LMS algorithm compared to the RLS algorithm?

a: LMS has lower computational complexity b: LMS has higher computational complexity c: LMS and RLS have similar computational complexity d: LMS and RLS have no computational complexity

In autoregressive models ……………………………

a: Current value of dependent variable is influenced by current values of independent variables b: Current value of dependent variable is influenced by current and past values of independent variables c: Current value of dependent variable is influenced by past values of both dependent and independent variables d: None of the above

A white noise process will have

a: (ii) and (iv) only b: (i) and (iii) only c: (i), (ii) and (iii) only d: (i), (ii), (iii) and (iv)

The white noise spectral density………………………

a: Changes with frequency b: Remain constant c: Changes with BW d: Changes with amplitude

What are the properties of autoregressive Models?

a: Stationarity b: Invertibility c: Ergodicity d: All of the above

What is the key feature of an order (p) of AR model?

a: The current value depends on future values b: The current value depends only on a random noise term c: The current value depends on past p values d: The current value depends on the mean of the process

What is the standard form of WSSRP?

a: Wide Sense Stationary Random Points b: Wide Sense Stationary Random Particles c: Wide Sense Stationary Random Process d: None of the above

Gaussian process is a

a: Wide sense stationary process b: Strict sense stationary process c: All of the mentioned d: None of the mentioned

Random variables give relationship between _____

a: Two random events b: Probability of occurrence of two random events c: Random event and a real number d: Random event and its probability of occurrence

A stationary stochastic process has

a: Finite energy signal b: Infinite zero signal c: Zero energy signal d: None of the mentioned

Which of the following conditions are necessary for a series to be classifiable as a weakly stationary process?

a: (ii) and (iv) only b: (i) and (iii) only c: (i), (ii) and (iii) only d: (i), (ii), (iii) and (iv)