Efficient Predefined-Time Adaptive Neural Networks for Computing Time-Varying Tensor Moore-Penrose Inverse.

This article proposes predefined-time adaptive neural network (PTANN) and event-triggered PTANN (ET-PTANN) models to efficiently compute the time-varying tensor Moore-Penrose (MP) inverse. The PTANN model incorporates a novel adaptive parameter and activation function, enabling it to achieve strongly predefined-time convergence. Unlike traditional time-varying parameters that increase over time, the adaptive parameter is proportional to the error norm, thereby better allocating computational resources and improving efficiency.

Predefined-Time Zeroing Neural Networks With Independent Prior Parameter for Solving Time-Varying Plural Lyapunov Tensor Equation.

As an extension of the Lyapunov equation, the time-varying plural Lyapunov tensor equation (TV-PLTE) can carry multidimensional data, which can be solved by zeroing neural network (ZNN) models effectively. However, existing ZNN models only focus on time-varying equations in field of real number. Besides, the upper bound of the settling time depends on the value of ZNN model parameters, which is a conservative estimation for existing ZNN models.

A TDF-WNSP-WLFM algorithm for product recommendation based on multiple types of implicit user behavior.

E-commerce platforms usually train their recommender system models to achieve personalized recommendations based on user behavior data. User behavior can be categorized into implicit and explicit feedback. Explicit feedback data have been well studied.

Novel Protein Sequence Comparison Method Based on Transition Probability Graph and Information Entropy.

Aim And Objective: Aim and Objective: Sequence analysis is one of the foundations in bioinformatics. It is widely used to find out the feature metrics hidden in the sequence. Otherwise, the graphical representation of the biologic sequence is an important tool for sequencing analysis.

Recent Advances on Prediction of Human Papillomaviruses Risk Types.

Background: Some studies have shown that Human Papillomavirus (HPV) is strongly associated with cervical cancer. As we all know, cervical cancer still remains the fourth most common cancer, affecting women worldwide. Thus, it is both challenging and essential to detect risk types of human papillomaviruses.

Novel Method of 3-Dimensional Graphical Representation for Proteins and Its Application.

In this article, we propose a 3-dimensional graphical representation of protein sequences based on 10 physicochemical properties of 20 amino acids and the BLOSUM62 matrix. It contains evolutionary information and provides intuitive visualization. To further analyze the similarity of proteins, we extract a specific vector from the graphical representation curve.

A protein mapping method based on physicochemical properties and dimension reduction.

Background: The graphical mapping of a protein sequence is more difficult than the graphical mapping of a DNA sequence because of the twenty amino acids and their complicated physicochemical properties. However, the graphical mapping for protein sequences attracts many researchers to develop different mapping methods. Currently, researchers have proposed their mapping methods based on several physicochemical properties.

Two-step camera calibration method based on the SPGD algorithm.

Given the rapid convergence characteristic of the stochastic parallel gradient descent (SPGD) algorithm, this study proposes a method that applies the algorithm to a two-step camera calibration method to resolve the frequent iteration and long calibration time deficiencies that exist under the traditional two-step camera calibration method, thereby achieving rapid calibration. The method first uses image coordinates obtained with subpixel positioning technology as initial values of control variables, in addition to positive disturbances produced on a two-dimensional plane, then uses two-step theory to calculate the average value of aberrations. Based on the same rationale, negative disturbances are then produced and the average value of the aberrations is calculated.

Gene comparison based on the repetition of single-nucleotide structure patterns.

According to the repetition structure patterns of single-nucleotides, we propose a novel digital representation method to characterize primary DNA sequences. Based on this representation we give a new RP-SP (repeat and space) vector to compute the distance of different sequences. The examination of similarities/dissimilarities among different sequences illustrates the utility of the proposed RP-SP vector distance.

Application of 2D graphic representation of protein sequence based on Huffman tree method.

Based on Huffman tree method, we propose a new 2D graphic representation of protein sequence. This representation can completely avoid loss of information in the transfer of data from a protein sequence to its graphic representation. The method consists of two parts.

Using Huffman coding method to visualize and analyze DNA sequences.

On the basis of the Huffman coding method, we propose a new graphical representation of DNA sequence. The representation can avoid degeneracy and loss of information in the transfer of data from a DNA sequence to its graphical representation. Then a multicomponent vector from the representation is introduced to characterize quantitatively DNA sequences.

Self-similarity analysis of eubacteria genome based on weighted graph.

We introduce a weighted graph model to investigate the self-similarity characteristics of eubacteria genomes. The regular treating in similarity comparison about genome is to discover the evolution distance among different genomes. Few people focus their attention on the overall statistical characteristics of each gene compared with other genes in the same genome.

A combination dimensionality reduction approach to codon position patterns of eubacteria based on their complete genomes.

Graphical techniques have become powerful tools for the visualization and analysis of complicated biological systems. However, we cannot give such a graphical representation in a 2D/3D space when the dimensions of the represented data are more than three dimensions. The proposed method, a combination dimensionality reduction approach (CDR), consists of two parts: (i) principal component analysis (PCA) with a newly defined parameter ρ and (ii) locally linear embedding (LLE) with a proposed graphical selection for its optional parameter k.

New method for global alignment of 2 DNA sequences by the tree data structure.

We introduce a new approach to investigate problem of DNA sequence alignment. The method consists of three parts: (i) simple alignment algorithm, (ii) extension algorithm for largest common substring, (iii) graphical simple alignment tree (GSA tree). The approach firstly obtains a graphical representation of scores of DNA sequences by the scoring equation R(0)*R-S(0)*S-T(0)*(a+bk).

Classification analysis of dual nucleotides using dimension reduction.

We introduce a new approach to investigate the dual nucleotides compositions of 11 Gram-positive and 12 Gram-negative eubacteria recently studied by Sorimachi and Okayasu. The approach firstly obtains a 16-dimension vector set of dual nucleotides by PN-curve from the complete genome of organism. Each vector of the set corresponds to a single gene of genome.

Numerical characterization of DNA sequences based on digital signal method.

Based on digital signal method, we propose a new representation of DNA primary sequence. The representation can completely avoid loss of information in the transfer of data from a DNA sequence to its mathematical representation. Afterwards, we suggest one such approach to reach quantification of similarities based on digital signal similarity theory.

New 3D graphical representation of DNA sequence based on dual nucleotides.

We introduce a 3D graphical representation of DNA sequences based on the pairs of dual nucleotides (DNs). Based on this representation, we consider some mathematical invariants and construct two 16-component vectors associated with these invariants. The vectors are used to characterize and compare the complete coding sequence part of beta globin gene of nine different species.