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Then, we apply the matrix to express the linear transformation layer of these block ciphers and give a detailed process.

An Upper Bound of the Longest Impossible Differentials of Several Block Ciphers

They cover the basics of probability theory, the digital features of random variables, methods of describing random signals, complex stochastic processes, the linear transformation of the stationary stochastic process, the stationary narrow band stochastic process, the nonlinear transformation method of stationary random processes, and the nonstationary stochastic process and methods of analyzing it in modern signal processing.

Random Signal Analysis

Linear transformation functions are applied on the overall partition of the fuzzy sets and will either linearly expand or contract all the fuzzy sets (see Figure 1).

Context Adaptation of Fuzzy Inference System-Based Construction Labor Productivity Models

For our purpose, the observation that ILI is required to register information in experience is vital, first because it means that the form of information in the sensory cortex, digital information, is not the form of information in experience, and second because just such a linear transformation would be required to convert the digital information in a sensory cortex into the kind of information, by which a critical instability on the cortex could represent it in experience.

Quantum fluctuation fields and conscious experience: How neurodynamics transcends classical and quantum mechanics

* The proposed HVS-based algorithm focuses on the three sub-models :maximum likelihood estimation method,blind deconvolution and dehazing using linear transformation.

Generic image quality assessment of portable fundus camera photographs

proposes a zero-dimensional Grobner basis construction method by choosing suitable term order and variable order after performing an in-depth study on the linear transformation and the system of multivariate polynomial equations of AES-256.

Advanced Information Technology Convergence 2017

Namely, linear transformation matrix learned in the high dimensional feature space can more appropriately map samples into their class labels and has more powerful discriminating ability.

Kernel Negative [epsilon] Dragging Linear Regression for Pattern Classification

So, the name of the transition matrix of the state is quite suitable for a matrix [PHI][t.sub.0]), as it reflects the state of the system at the moment [t.sub.0] with the help of a linear transformation:

Speeded search of the periodic processes of dynamical systems