Perfect Reconstructable Decimated One-Dimensional Empirical Mode Decomposition Filter Banks

This paper introduces decimated filter banks for the one-dimensional empirical mode decomposition （1D-EMD）. These filter banks can provide perfect reconstruction and allow for an arbitrary tree structure. Since the EMD is a data driven decomposition, it is a very useful analysis instrument for non-stationary and non-linear signals. However, the traditional 1D-EMD has the disadvantage of expanding the data. Large data sets can be generated as the amount of data to be stored increases with every decomposition level. The 1D-EMD can be thought as having the structure of a single dyadic filter. However, a methodology to incorporate the decomposition into any arbitrary tree structure has not been reported yet in the literature. This paper shows how to extend the 1D-EMD into any arbitrary tree structure while maintaining the perfect reconstruction property. Furthermore, the technique allows for downsampling the decomposed signals. This paper, thus, presents a method to minimize the data-expansion drawback of the 1D-EMD by using decimation and merging the EMD coefficients. The proposed algorithm is applicable for any arbitrary tree structure including a full binary tree structure.

The Cumulative Method for Multiplication and Division

This paper provides a method of the process of computation called the cumulative method, it is based upon repeated cumulative process. The cumulative method is being adapted to the purposes of computation, particularly multiplication and division. The operations of multiplication and division are represented by algebraic formulas. An advantage of the method is that the cumulative process can be performed on decimal numbers. The present paper aims to establish a basic and useful formula valid for the two fundamental arithmetic operations of multiplication and division. The new cumulative method proved to be more flexible and made it possible to extend the multiplication and division based on repeated addition/subtraction to decimal numbers.

Low-Complexity Integrated Super-Resolution Sensing and Communication with Signal Decimation and Ambiguity Removal

Integrated sensing and communication(ISAC)is one of the main usage scenarios for 6G wireless networks.To most efficiently utilize the limited wireless resources,integrated super-resolution sensing and communication(ISSAC)has been recently proposed to significantly improve sensing performance with super-resolution algorithms for ISAC systems,such as the Multiple Signal Classification(MUSIC)algorithm.However,traditional super-resolution sensing algorithms suffer from prohibitive computational complexity of orthogonal-frequency division multiplexing(OFDM)systems due to the large dimensions of the signals in the subcarrier and symbol domains.To address such issues,we propose a novel two-stage approach to reduce the computational complexity for super-resolution range estimation significantly.The key idea of the proposed scheme is to first uniformly decimate signals in the subcarrier domain so that the computational complexity is significantly reduced without missing any target in the range domain.However,the decimation operation may result in range ambiguity due to pseudo peaks,which is addressed by the second stage where the total collocated subcarrier data are used to verify the detected peaks.Compared with traditional MUSIC algorithms,the proposed scheme reduces computational complexity by two orders of magnitude,while maintaining the range resolution and unambiguity.Simulation results verify the effectiveness of the proposed scheme.

Enhanced Wideband Frequency Estimation via FFT: Leveraging Polynomial Interpolation and Array Indexing

Accurate frequency estimation in a wideband digital receiver using the FFT algorithm encounters challenges, such as spectral leakage resulting from the FFT’s assumption of signal periodicity. High-resolution FFTs pose computational demands, and estimating non-integer multiples of frequency resolution proves exceptionally challenging. This paper introduces two novel methods for enhanced frequency precision: polynomial interpolation and array indexing, comparing their results with super-resolution and scalloping loss. Simulation results demonstrate the effectiveness of the proposed methods in contemporary radar systems, with array indexing providing the best frequency estimation despite utilizing maximum hardware resources. The paper demonstrates a trade-off between accurate frequency estimation and hardware resources when comparing polynomial interpolation and array indexing.

An optimized infinite time-evolving block decimation algorithm for lattice systems

The infinite time-evolving block decimation algorithm(i TEBD)provides an efficient way to determine the ground state and dynamics of the quantum lattice systems in the thermodynamic limit.In this paper we suggest an optimized way to take the i TEBD calculation,which takes advantage of additional reduced decompositions to speed up the calculation.The numerical calculations show that for a comparable computation time our method provides more accurate results than the traditional i TEBD,especially for lattice systems with large on-site degrees of freedom.

线性反馈移位寄存器的差分能量攻击

能否有效去除算法噪声的影响,直接关系到能量攻击成败。该文以线性反馈移位寄存器(LFSR)相邻两个时钟周期的能量消耗差异为出发点,提出了一种新的差分能量攻击算法。它从根本上去除了密码算法噪声在攻击过程中带来的影响。由于该算法随机选择初始向量(initialization vector),从而使攻击者能够容易地将其推广到具有类似结构的流密码体制。为了进一步验证攻击算法的有效性,该文利用软件仿真的方法对DECIM进行了模拟攻击。仿真结果表明,该攻击算法能够有效降低LFSR的密钥搜索的复杂度。

A 16 bit Stereo Audio ΣΔ A/D Converter

A 16 bit stereo audio novel stability fifth-order ∑△ A/D converter that consists of switched capacitor ∑△ modulators, a decimation filter, and a bandgap circuit is proposed. A method for the stabilization of a high order single stage ∑△ modulator is also proposed. A new multistage comb filter is used for the front end decimation filter. The ∑△ A/D converter achieves a peak SNR of 96dB and a dynamic range of 96dB. The ADC was implemented in 0. 5μm 5V CMOS technology. The chip die area occupies only 4. 1mm × 2.4mm and dissipates 90mW.

A 16bit 96kHz Chopper-Stabilized Sigma-Delta ADC

A 16bit sigma-delta audio analog-to-digital converter is developed.It consists of an analog modulator and a digital decimator.A standard 2-order single-loop architecture is employed in the modulator.Chopper stabilization is applied to the first integrator to eliminate the 1/f noise.A low-power,area-efficient decimator is used,which includes a poly-phase comb-filter and a wave-digital-filter.The converter achieves a 92dB dynamic range over the 96kHz audio band.This single chip occupies 2.68mm2 in a 0.18μm six-metal CMOS process and dissipates only 15.5mW power.

New method to implement digital down converter in radar system

Digital down converter （DDC） is the main part of the next generation high frequency （HF） radar. In order to realize the single chip integrations of digital receiver hardware in the next generation HF Radar, a new design for DDC by using FPGA is presented. Some important and practical applications are given in this paper, and the result can prove the validity. Because we can adjust the parameters freely according to our need, the DDC system can be adapted to the next generation HF radar system.

Design of area and power efficient Radix-4 DIT FFT butterfly unit using floating point fused arithmetic

In this work, power efficient butterfly unit based FFT architecture is presented. The butterfly unit is designed using floating-point fused arithmetic units. The fused arithmetic units include two-term dot product unit and add-subtract unit. In these arithmetic units, operations are performed over complex data values. A modified fused floating-point two-term dot product and an enhanced model for the Radix-4 FFT butterfly unit are proposed. The modified fused two-term dot product is designed using Radix-16 booth multiplier. Radix-16 booth multiplier will reduce the switching activities compared to Radix-8 booth multiplier in existing system and also will reduce the area required. The proposed architecture is implemented efficiently for Radix-4 decimation in time(DIT) FFT butterfly with the two floating-point fused arithmetic units. The proposed enhanced architecture is synthesized, implemented, placed and routed on a FPGA device using Xilinx ISE tool. It is observed that the Radix-4 DIT fused floating-point FFT butterfly requires 50.17% less space and 12.16% reduced power compared to the existing methods and the proposed enhanced model requires 49.82% less space on the FPGA device compared to the proposed design. Also, reduced power consumption is addressed by utilizing the reusability technique, which results in 11.42% of power reduction of the enhanced model compared to the proposed design.

2-D MULTIRATE ALGORITHMS FOR EFFICIENT IMPLEMENTATION OF EDGE DETECTION

Edge detection is a fundamental issue in image analysis. This paper proposes multirate algorithms for efficient implementation of edge detector, and a design example is illustrated.The multirate (decimation and/or interpolation) signal processing algorithms can achieve considerable savings in computation and storage. The proposed algorithms result in mapping relations of their z-transfer functions between non-multirate and multirate mathematical expressions in terms of time-varying coefficient instead of traditional polyphase decomposition counterparts.The mapping properties can be readily utilized to efficiently analyze and synthesize multirate edge detection filters. The Very high-speed Hardware Description Language (VHDL) simulation results verify efficiency of the algorithms for real-time Field Programmable Gate-Array (FPGA)implementation.

LS-SVM and Monte Carlo methods based reliability analysis for settlement of soft clayey foundation

A method which adopts the combination of least squares support vector machine（LS-SVM） and Monte Carlo（MC） simulation is used to calculate the foundation settlement reliability.When using LS-SVM,choosing the training dataset and the values for LS-SVM parameters is the key.In a representative sense,the orthogonal experimental design with four factors and five levels is used to choose the inputs of the training dataset,and the outputs are calculated by using fast Lagrangian analysis continua（FLAC）.The decimal ant colony algorithm（DACA） is also used to determine the parameters.Calculation results show that the values of the two parameters,and δ2 have great effect on the performance of LS-SVM.After the training of LS-SVM,the inputs are sampled according to the probabilistic distribution,and the outputs are predicted with the trained LS-SVM,thus the reliability analysis can be performed by the MC method.A program compiled by Matlab is employed to calculate its reliability.Results show that the method of combining LS-SVM and MC simulation is applicable to the reliability analysis of soft foundation settlement.

Automatic Classification of Swedish Metadata Using Dewey Decimal Classification:A Comparison of Approaches

Purpose:With more and more digital collections of various information resources becoming available,also increasing is the challenge of assigning subject index terms and classes from quality knowledge organization systems.While the ultimate purpose is to understand the value of automatically produced Dewey Decimal Classification(DDC)classes for Swedish digital collections,the paper aims to evaluate the performance of six machine learning algorithms as well as a string-matching algorithm based on characteristics of DDC.Design/methodology/approach:State-of-the-art machine learning algorithms require at least 1,000 training examples per class.The complete data set at the time of research involved 143,838 records which had to be reduced to top three hierarchical levels of DDC in order to provide sufficient training data(totaling 802 classes in the training and testing sample,out of 14,413 classes at all levels).Findings:Evaluation shows that Support Vector Machine with linear kernel outperforms other machine learning algorithms as well as the string-matching algorithm on average;the string-matching algorithm outperforms machine learning for specific classes when characteristics of DDC are most suitable for the task.Word embeddings combined with different types of neural networks(simple linear network,standard neural network,1 D convolutional neural network,and recurrent neural network)produced worse results than Support Vector Machine,but reach close results,with the benefit of a smaller representation size.Impact of features in machine learning shows that using keywords or combining titles and keywords gives better results than using only titles as input.Stemming only marginally improves the results.Removed stop-words reduced accuracy in most cases,while removing less frequent words increased it marginally.The greatest impact is produced by the number of training examples:81.90%accuracy on the training set is achieved when at least 1,000 records per class are available in the training set,and 66.13%when too few records(often less than A Comparison of Approaches100 per class)on which to train are available—and these hold only for top 3 hierarchical levels(803 instead of 14,413 classes).Research limitations:Having to reduce the number of hierarchical levels to top three levels of DDC because of the lack of training data for all classes,skews the results so that they work in experimental conditions but barely for end users in operational retrieval systems.Practical implications:In conclusion,for operative information retrieval systems applying purely automatic DDC does not work,either using machine learning(because of the lack of training data for the large number of DDC classes)or using string-matching algorithm(because DDC characteristics perform well for automatic classification only in a small number of classes).Over time,more training examples may become available,and DDC may be enriched with synonyms in order to enhance accuracy of automatic classification which may also benefit information retrieval performance based on DDC.In order for quality information services to reach the objective of highest possible precision and recall,automatic classification should never be implemented on its own;instead,machine-aided indexing that combines the efficiency of automatic suggestions with quality of human decisions at the final stage should be the way for the future.Originality/value:The study explored machine learning on a large classification system of over 14,000 classes which is used in operational information retrieval systems.Due to lack of sufficient training data across the entire set of classes,an approach complementing machine learning,that of string matching,was applied.This combination should be explored further since it provides the potential for real-life applications with large target classification systems.

On design of efficient comb decimator with improved response

A three-part comb decimator is presented in this paper, for the applications with severe requirements of circuit performance and frequency response. Based on the modified prime factorization method and multistage polyphase decomposition, an efficient non-recursive structure for the cascaded integrator-comb （CIC） decimation filter is derived. Utilizing this structure as the core part, the proposed comb decimator can not only loosen the decimation ratio＇s limitation, but also balance the tradeoff among the overall power consumption, circuit area and maximum speed. Further, to improve the frequency response of the comb decimator, a cos-prefilter is introduced as the preprocessing part for increasing the aliasing rejection, and an optimum sin-based filter is used as the compensation part for decreasing the passband droop.

CONSTRUCTION OF SOME KIESSWETTER-LIKE FUNCTIONS-THE CONTINUOUS BUT NON-DIFFERENT-IABLE FUNCTION DEFINED BY QUINARY DECIMAL

In this paper, we construct some continuous but non-differentiable functions defined by quinary dec-imal, that are Kiesswetter-like functions. We discuss their properties, then investigate the Hausdorff dimensions of graphs of these functions and give a detailed proof.

颅骨切除减压治疗恶性大脑中动脉梗死试验(DECIMAL)

试验状态:从2003年11月开始,已纳入18例患者。试验目的:评价偏侧颅骨切除减压和硬膜成形术在恶性大脑中动脉(MCA)区梗死患者中的作用。试验设计:多中心随机对照试验。

Low complexity reconfigurable architecture for the 5/3 and 9/7 discrete wavelet transform

Efficient reconfigurable VLSI architecture for 1-D 5/3 and 9/7 wavelet transforms adopted in JPEG2000 proposal, based on lifting scheme is proposed. The embedded decimation technique based on fold and time multiplexing, as well as embedded boundary data extension technique, is adopted to optimize the design of the architecture. These reduce significantly the required numbers of the multipliers, adders and registers, as well as the amount of accessing external memory, and lead to decrease efficiently the hardware cost and power consumption of the design. The architecture is designed to generate an output per clock cycle, and the detailed component and the approximation of the input signal are available alternately. Experimental simulation and comparison results are presented, which demonstrate that the proposed architecture has lower hardware complexity, thus it is adapted for embedded applications. The presented architecture is simple, regular and scalable, and well suited for VLSI implementation.

A comparison of mapping strategies from DDC to CLC

Purpose: This study aims to discuss the strategies for mapping from Dewey Decimal Classification(DDC) numbers to Chinese Library Classification(CLC) numbers based on co-occurrence mapping while minimizing manual intervention.Design/methodology/approach: Several statistical tables were created based on frequency counts of the mapping relations with samples of USMARC records,which contain both DDC and CLC numbers. A manual table was created through direct mapping. In order to find reasonable mapping strategies,the mapping results were compared from three aspects including the sample size,the choice between one-to-one and one-to-multiple mapping relations,and the role of a manual mapping table.Findings: Larger sample size provides more DDC numbers in the mapping table. The statistical table including one-to-multiple DDC-CLC relations provides a higher ratio of correct matches than that including only one-to-one relations. The manual mapping table cannot produce a better result than the statistical tables. Therefore,we should make full use of statistical mapping tables and avoid the time-consuming manual mapping as much as possible.Research limitations: All the sample sizes were small. We did not consider DDC editions in our study. One-to-multiple DDC-CLC relations in the records were collected in the mapping table,but how to select one appropriate CLC number in the matching process needs to be further studied.Practical implications: The ratio of correct matches based on the statistical mapping table came up to about 90% by CLC top-level classes and 76% by the second-level classes in our study. The statistical mapping table will be improved to realize the automatic classification of e-resources and shorten the cataloging cycle significantly.Originality/value: The mapping results were investigated from different aspects in order to find suitable mapping strategies from DDC to CLC while minimizing manual intervention.The findings have facilitated the establishment of DDC-CLC mapping system for practical applications.

Dynamical signatures of the one-dimensional deconfined quantum critical point

We study the critical scaling and dynamical signatures of fractionalized excitations at two different deconfined quantum critical points(DQCPs)in an S=1/2 spin chain using the time evolution of infinite matrix product states.The scaling of the correlation functions and the dispersion of the conserved current correlations explicitly show the emergence of enhanced continuous symmetries at these DQCPs.The dynamical structure factors in several different channels reveal the development of deconfined fractionalized excitations at the DQCPs.Furthermore,we find an effective spin-charge separation at the DQCP between the ferromagnetic(FM)and valence bond solid(VBS)phases,and identify two continua associated with different types of fractionalized excitations at the DQCP between the X-direction and Z-direction FM phases.Our findings not only provide direct evidence for the DQCP in one dimension but also shed light on exploring the DQCP in higher dimensions.

A New Evolutionary Algorithm Based on the Decimal Coding

Traditional Evolutionary Algorithm (EAs) is based on the binary code, real number code, structure code and so on. But these coding strategies have their own advantages and disadvantages for the optimization of functions. In this paper a new Decimal Coding Strategy (DCS), which is convenient for space division and alterable precision, was proposed, and the theory analysis of its implicit parallelism and convergence was also discussed. We also redesign several genetic operators for the decimal code. In order to utilize the historial information of the existing individuals in the process of evolution and avoid repeated exploring, the strategies of space shrinking and precision alterable, are adopted. Finally, the evolutionary algorithm based on decimal coding (DCEAs) was applied to the optimization of functions, the optimization of parameter, mixed-integer nonlinear programming. Comparison with traditional GAs was made and the experimental results show that the performances of DCEAS are better than the tradition GAs.