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In this matrix, each row represents one of the three parity-check constraints, while each column represents one of the six bits in the received codeword. In this example, the eight codewords can be obtained by putting the parity-check matrix H into this form [ − P T | I n − k ] {\displaystyle {\begin{bmatrix}-P^{T}|I_{n-k}\end{bmatrix ...
The block length of a block code is the number of symbols in a block. Hence, the elements c {\displaystyle c} of Σ n {\displaystyle \Sigma ^{n}} are strings of length n {\displaystyle n} and correspond to blocks that may be received by the receiver.
print length([2+1, 3*2, 1/0, 5-4]) fails under strict evaluation because of the division by zero in the third element of the list. Under lazy evaluation, the length function returns the value 4 (i.e., the number of items in the list), since evaluating it does not attempt to evaluate the terms making up the list.
DELETE requires a shared table lock; Triggers fire; DELETE can be used in the case of: database link; DELETE returns the number of records deleted; Transaction log - DELETE needs to read records, check constraints, update block, update indexes, and generate redo / undo. All of this takes time, hence it takes time much longer than with TRUNCATE
Python does not contain the classical for loop, rather a foreach loop is used to iterate over the output of the built-in range() function which returns an iterable sequence of integers. for i in range ( 1 , 6 ): # gives i values from 1 to 5 inclusive (but not 6) # statements print ( i ) # if we want 6 we must do the following for i in range ( 1 ...
Kernel density estimation of 100 normally distributed random numbers using different smoothing bandwidths.. In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as weights.
MATLAB – The SVD function is part of the basic system. In the Statistics Toolbox, the functions princomp and pca (R2012b) give the principal components, while the function pcares gives the residuals and reconstructed matrix for a low-rank PCA approximation. Matplotlib – Python library have a PCA package in the .mlab module.
[33] [34] The GNU Octave and Matlab code used to calculate the noise covariance matrices using the ALS technique is available online using the GNU General Public License. [35] Field Kalman Filter (FKF), a Bayesian algorithm, which allows simultaneous estimation of the state, parameters and noise covariance has been proposed. [36]