A Single Matrix Representation for General Digital Filter Structures [Lecture Notes

A control centric analysis and design of the low drop out (LDO) voltage regulator is presented in this work. The design complexity involving interdependence of regulating loop in frequency domain and the performance parameters for voltage regulator is simplified for intuition by the development of signal flow graph (SFG). A model based on the SFG is developed and tested in Matlab/Simulink environment for a desired time and frequency domain specification. Time domain optimisation for a given steady state accuracy and settling is formulated based on the developed model.

The detection of regulatory sequences in DNA is a challenging problem, especially when considered in the context of whole genomes. The degree of sequence conservation of regulatory protein binding sites is often weak, and the sites are obscured by surrounding intergenic sequence. Since structural interactions are vital for protein-DNA interactions, structural representations of regulatory sites can yield a more accurate model and a better understanding of within-site variability. However, the use of multiple alternative representations of DNA introduces a requirement for novel algorithms that can create and test different combinations of DNA features. The Genetic Algorithm Neural Network (GANN) was designed to identify combinations of patterns that can be used to distinguish between different classes of training sequence. GANN trains a set of artificial neural networks to classify sets of sequence using either backpropagation or a genetic algorithm, and uses an ‘outer genetic algorithm’ to choose the best inputs from a pool of DNA features that can include sequence, structure, and weight matrix representations. When trained with a subset of upstream sequences from a whole genome, GANN was able to detect patterns such as the Shine-Dalgarno sequence in Escherichia coli K12, and sequences consistent with archaeal promoters in the archaeon Sulfolobus solfataricus P2. The Motif Genetic Algorithm (MGA) constructs motif representations by concatenating minimal units of DNA sequence and structure. This algorithm was used to model conserved patterns in DNA, including the binding sites for E. coli cyclic AMP activated protein (CAP), integration host factor (IHF), and two different promoter types recognized by alternative bacterial sigma factors. The CAP models were used to detect other putative binding sites in upstream regions of the E. coli K12 genome, while attempts to train an accurate model of IHF binding sites revealed an important role for structural representations in motif modeling.

Automatic Control Systems, Block Diagrams, and Signal Flow Graphs

Fast periodic graph exploration with constant memory

Artificial noise (AN) is one of physical layer security techniques, which can realize secure communication. AN is a noise signal which is intentionally transmitted from transmitter along with data signals. Since AN is generated to be canceled out at legitimate receivers, it can prevent eavesdroppers from eavesdropping even if transmitters do not know the existence of eavesdroppers. In spite of its usefulness, most of the AN generation techniques cannot be applied to multiple-input multiple-output (MIMO) systems when the number of antennas at the transmitter is less than that at the legitimate receiver. In this paper, we consider time-domain AN generation techniques for MIMO orthogonal frequency division multiplexing (OFDM) systems. A time-domain AN generation technique is originally proposed for single-input single-output (SISO) OFDM systems. Thus, we first consider to apply the conventional time-domain AN generation technique to MIMO-OFDM systems, and show that this technique requires a large number of antennas at the transmitter and/or a longer cyclic prefix (CP). Next, to solve this problem, we propose another time-domain AN generation technique. Our proposed time-domain AN is generated to be canceled out at the legitimate receiver in the frequency domain, while the conventional time-domain AN is canceled out in the time domain. As a result, the proposed time-domain AN generation technique can be applied to MIMO-OFDM systems, irrespective of the number of antennas and the length of CP. Simulation results can show that the proposed AN achieves the same secrecy rate as the conventional time-domain AN. Moreover, the proposed technique achieves a higher secrecy rate when a MIMO-OFDM system is employed with the antenna configuration to which the conventional time-domain AN generation technique is hard to be applied.

A signal-processing software system is described which allows the simulation of systems described by block diagrams or signal-flow graphs. A high-level data-flow language describes the interconnection of the components. All configurations of interconnections are allowed, including those containing feedback. Component systems (blocks) are allowed to be multi-input, multi-output, and to be programmed in any language. Blocks are implemented as separate processes running under a UNIX2 operating system. Input and output signals are transferred between blocks via the UNIXpipe facility. Thedata type of a signal is arbitrary in the context of the compiler; within a component or system, signals and internal variables can be either floating point or fixed point. The compiler enforces strong or weak type checking of signals according to the characteristics of the blocks generating and receiving the signals. The invariance of the program to implementation data type is accomplished by the use of abstract data types. Fixed-point simulations having differing number of bits per signal and per internal variable in a block are supported. Special display software is used to allow any signal in the system to be displayed on any graphics device.

Features in the design of a graphical man-machine interface for pre-processing the inputs to computer-aided control system design software are described in this paper. The primary objective is to allow the control engineer to communicate with a modem graphics workstation in a natural, familiar and friendly way, by means of block diagrams, signal flow graphs and standard mathematical text. Graphical methods for the input and output of these are described. Transformations between different system descriptions are considered which allow all algebraic manipulations and reductions to be performed on signal flow graphs. For these manipulations, rule-based methods are shown to be effective. The possibility of using symbolic computation languages for algebraic operations is also considered.

LINEAR CIRCUIT ANALYSIS. Fundamental Circuit Concepts. Network Laws and Theorems. Terminal and Port Representation. Signal Flow Graphs in Filter Analysis and Synthesis. Analysis in the Frequency Domain. Tableau and Modified Nodal Formulations. Frequency Domain Methods. Symbolic Analysis. Analysis in the Time Domain. State-Variable Techniques. FEEDBACK CIRCUITS. Feedback Amplifier Theory. Feedback Amplifier Configurations. General Feedback Theory. The Network Functions and Feedback. Measurement of Return Difference. Multiple-Loop Feedback Amplifiers. Index.

BackgroundSequence matching is extremely important for applications throughout biology, particularly for discovering information such as functional and evolutionary relationships, and also for discriminating between unimportant and disease mutants. At present the functions of a large fraction of genes are unknown; improvements in sequence matching will improve gene annotations. Universal amino acid substitution matrices such as Blosum62 are used to measure sequence similarities and to identify distant homologues, regardless of the structure class. However, such single matrices do not take into account important structural information evident within the different topologies of proteins and treats substitutions within all protein folds identically. Others have suggested that the use of structural information can lead to significant improvements in sequence matching but this has not yet been very effective. Here we develop novel substitution matrices that include not only general sequence information but also have a topology specific component that is unique for each CATH topology. This novel feature of using a combination of sequence and structure information for each protein topology significantly improves the sequence matching scores for the sequence pairs tested. We have used a novel multi-structure alignment method for each homology level of CATH in order to extract topological information.ResultsWe obtain statistically significant improved sequence matching scores for 73 % of the alpha helical test cases. On average, 61 % of the test cases showed improvements in homology detection when structure information was incorporated into the substitution matrices. On average z-scores for homology detection are improved by more than 54 % for all cases, and some individual cases have z-scores more than twice those obtained using generic matrices. Our topology specific similarity matrices also outperform other traditional similarity matrices and single matrix based structure methods. When default amino acid substitution matrix in the Psi-blast algorithm is replaced by our structure-based matrices, the structure matching is significantly improved over conventional Psi-blast. It also outperforms results obtained for the corresponding HMM profiles generated for each topology.ConclusionsWe show that by incorporating topology-specific structure information in addition to sequence information into specific amino acid substitution matrices, the sequence matching scores and homology detection are significantly improved. Our topology specific similarity matrices outperform other traditional similarity matrices, single matrix based structure methods, also show improvement over conventional Psi-blast and HMM profile based methods in sequence matching. The results support the discriminatory ability of the new amino acid similarity matrices to distinguish between distant homologs and structurally dissimilar pairs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1198-z) contains supplementary material, which is available to authorized users.

formula omitted] model checking for time Petri nets

Scientists and engineer are being encountered regularly with the workout, analysis and amalgam of real-life complications. The component of an actual framework can be broken down by the arrangement of differential conditions from which complex model of high order can be obtained in the state space structure or in transfer function form which are called frequency domain representation or time domain, respectively. Difficulties may be posed by a mathematical model of high order in its amalgam, analysis and recognition. Thus, a demand occurs for an organized method to develop a reduced model which preserves the main subjective properties of high-order framework like steadiness, dependability, good time and frequency response matching as in the original framework. Model reduction helps in simplifying the system, reduces computational efforts and makes the design of the controller numerically more efficient. This work is encouraged by nature-based algorithm for order reduction by grey wolf optimization. This algorithm mimes the ranking-based leadership and hunting conduct of grey wolves. The ranking-based leadership is simulated by employing four types of grey wolves such as alpha, beta, delta and omega. Grey wolf optimization technique is used for determining the denominator polynomial of the reduced model, while Pade approximation technique is used for finding the numerator polynomial. The approach is proposed for both single input single output (SISO) and multi-input multi-output (MIMO) systems. This technique assures the stable reduced models of stable systems. The technique is protracted to the issue of reducing a high-order multivariable system defined by its matrix transfer function. Some examples from the literature are taken for illustrating the feasibility of the method. ISE has been taken as target work for looking at the performance of the proposed strategy with other existing techniques in the writing.KeywordsStabilityGrey wolf optimizationTransfer functionPade approximationOrder reduction

It is shown in this paper that any state space realization (A, b, c) of a given transfer function T(s) = β(s/α(s with α(s) monic and dim(A) = deg(α(s)), satisfies the identity β(A) = Qc(A, b)SαQo(A, c) where Qc(A, b) and Qo(A, c) are the controllability matrix and observability matrix of the matrix triple (A, b, c), respectively, and Sα is a nonsingular symmetric matrix. Such an identity gives a deep relationship between the state space description and the transfer function description of single-input single-output (SISO) linear systems. As a direct conclusion, we arrive at the well-known result that a realization of any transfer function is minimal if and only if the numerator and the denominator of the transfer function is coprime. Such a result is also extended to the SISO descriptor linear system case. As an applications, a complete solution to the commuting matrix equation AX = XA is proposed and the minimal realization of multi-input multi-output (MIMO) linear system is considered.

This article aims to propose a novel analytical model for anisotropic multi-layer elliptical structures incorporating graphene layers. The multi-layer structure is formed of various magnetic materials, and each one has the permittivity and permeability tensors of ε̅̅ and μ̅, respectively. An external magnetic bias has been applied in the axial direction. A graphene layer, with isotropic surface conductivity of o, has been sandwiched between the two adjacent anisotropic materials. A novel matrix representation has been derived to find the propagation parameters of the multi-layer structure. Two exemplary important cases of the proposed general structure, as waveguides, have been investigated to show, first, the validity of our proposed analytical model and second, the richness of the general structure. The analytical and simulation results show an excellent agreement. A very large value of figure of merit (FOM), e.g., FOM = 110, is achieved for the second structure for the chemical potential and external magnetic bias of μ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> = 0.9 eV and B <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> = 1 T, respectively. Our general structure and its analytical model can be exploited to design innovative terahertz devices such as absorbers, couplers, and cloaks.

Linear regressive realizations of LTI state space models

Clustering Web services can improve the quality and efficiency of service discovery and management within a service repository. Nowadays, Web services frequently interact (e.g., composition relation and tag sharing relation) with each other to form a complex and heterogeneous service relationship network. The rich network relations inherently reflect either positive or negative clustering association between Web services, which can be a strong supplement to service semantics for characterizing functional affinities between Web services. In this paper, we propose to cluster Web services by utilizing both description documents and the structural information from the service relationship network. We first learn the content semantic information from service description documents based on the widely used Doc2vec model, and meanwhile, learn the structural semantic information from the service relationship network based on a network representation learning algorithm. Then, we propose to pretrain the content and structural semantic information to obtain the most relevant and unified features through training a service classification model with partially labeled data. Finally, a spectral clustering algorithm is utilized for Web services clustering based on the above unified features with preserved content and structural semantics. Therefore, the proposed services clustering approach takes advantage of both service content semantic and service network structure semantic based similarity between services. Extensive experiments are conducted on a real-world dataset from ProgrammableWeb, composed of 12919 Web API services. Experimental results demonstrate that our approach yields an improvement of 4.78% in precision and 5.4% in recall over the state-of-the-art method.