Sparse Matrix-Dense Matrix Multiplication (SpMM) is a crucial kernel used in a wide range of fields including machine learning and linear algebra solvers. thus, enhancing the performance of SpMM is essential. the unev...
详细信息
this article provides a detailed overview of the process of implementing an FIR digital filter using the TI TMS320 series DSP platform withthe C programming language. It covers topics such as the working principle of...
详细信息
ISBN:
(数字)9798350352719
ISBN:
(纸本)9798350352726
this article provides a detailed overview of the process of implementing an FIR digital filter using the TI TMS320 series DSP platform withthe C programming language. It covers topics such as the working principle of FIR filters, design methods, DSP development environment setup, C code implementation, simulation verification, and system testing. through simulation verification, the frequency response characteristics of the FIR filter are confirmed, and the system testing results demonstrate that the FIR filter achieves effective signal filtering under appropriate conditions with accurate frequency response and high signal-to-noise ratio. this document comprehensively validates the excellent signal processing performance of FIR filters on the DSP platform, offering valuable insights for applications involving FIR filter design on DSP platforms.
In recent years, in addition to the growth in the number of investors in the stock market, there has been a growing interest in predicting stock prices. Accurate stock prices can effectively improve investment returns...
详细信息
ISBN:
(纸本)9781450399067
In recent years, in addition to the growth in the number of investors in the stock market, there has been a growing interest in predicting stock prices. Accurate stock prices can effectively improve investment returns on the premise of reducing investment risks for stock investors. therefore, this study presents a hybrid Bo-LSTM-SVR model to predict the next day's stock closing price. Firstly, the hyper-parameters of LSTM and SVR as well as the length of their respective sliding windows are optimized by the Bayesian optimization method, so as to obtain more accurate predicted values of the single models. the genetic algorithm is then adopted every day to decide the weight of the two single models, and finally, the combined predicted values are obtained. In order to ensure that the prediction of the proposed model is more accurate, this model and the other six models are applied to predict the closing prices of the Shanghai Composite Index on the next trading day. the results reveal that the model proposed in this study is the most accurate, withthe smallest MAE and RMSE as well as the largest R(boolean AND)2. Compared with other models, the proposed model is more suitable for stock price prediction, which provides a dependable tool for investors to make stock investment decisions.
Language-based colorization generates realistic and aesthetically appealing colors by leveraging the guidance of intuitive and user-friendly natural language descriptions. Previous methods in language-based image colo...
详细信息
As critical rotating machinery components, the monitoring of the health status and fault diagnosis of bearings become particularly important. In this paper, a bearing digital twin model and fault diagnosis system base...
详细信息
ISBN:
(数字)9798350352719
ISBN:
(纸本)9798350352726
As critical rotating machinery components, the monitoring of the health status and fault diagnosis of bearings become particularly important. In this paper, a bearing digital twin model and fault diagnosis system based on ANSYS and Matlab is proposed. First, a high-precision digital twin model of the bearing was constructed using ANSYS software, which can simulate the physical behavior of the bearing under different working conditions. Subsequently, a Matlab-based fault diagnosis system was developed, which is able to read vibration data automatically and extract fault features through an improved spectral cliff algorithm and deconvolution algorithm. the system is designed with a modular architecture, including key aspects such as data acquisition, signal preprocessing, feature extraction and fault diagnosis. the experimental results show that the proposed system outperforms the traditional methods in terms of the accuracy of fault detection and the efficiency of diagnosis.
the proceedings contain 33 papers. the special focus in this conference is on Applications of Fluid Dynamics. the topics include: Impact of Radiation on Flow of Copper-Water Nanofluid Squeezed Between parallel Plates ...
ISBN:
(纸本)9789811919282
the proceedings contain 33 papers. the special focus in this conference is on Applications of Fluid Dynamics. the topics include: Impact of Radiation on Flow of Copper-Water Nanofluid Squeezed Between parallel Plates Filled with Darcy Porous Medium;MHD Flow of Casson Nanofluid Over An Inclined Porous Stretching Surface;dispersion of Rayleigh Wave in a Shielded Anisotropic Generalized thermoelastic Layer;nonlinear Equation for Wave Motion with Undulated Bottom;numerical Study on Nanofluid Flow and Heat Transfer Over a thin Moving Needle with Arrhenius Pre-Exponential Factor Law and Slip Effect;effect of Magnetic Field on Unsteady Flow of Dusty Fluid Due to Constant Pressure Gradient through a Circular Cylinder: An Analytical Treatment;convective Flow over a Vertical Cone Embedded in a Stratified Medium by Group theoretical Method;peristaltic Flow of Ferromagnetic Fluid in a Vertical Slot with Mixed Convection;mathematical Modeling for Non-linear Wave Interaction of Submerged Body Using Hybrid Element Method;aligned Magnetic Field and Radiation Absorption Effects on Free Convection Chemically Reactive Flow Past An Inclined Surface;Investigating the Risk of Airborne COVID-19 and the Importance of Social Restrictions in Regulating the Transmission;a Numerical Algorithm Based on Tension Spline Scheme for Solving Singularly Perturbed Differential Difference Equations with Shifts;splines for Atmospheric Data;Dynamics of SEIR Model of Nipah Virus;thermodynamic Analysis of Cross-Flow Heat Exchanger with Organic Blends As Substitute to Ionic Coolants;modified Image processing Technique for Measurement of Intermittent Flow Characteristics;Modification of Surface Properties of AA7075 by Friction Stir processing;POD—ANN Reduced Order Macromodel of Nonlinear Autonomous Dissipative System Using Machine Learning.
Separating algorithms from their computation schedule has become a de facto solution to tackle the challenges of developing high performance code on modern heterogeneous architectures. Common approaches include Domain...
详细信息
this research work presents a detailed analysis on the design and implementation of parallel and cascade topologies in addition to the realization of high-speed FIR filters using FPGAs. An FPGA-based FIR filter's ...
this research work presents a detailed analysis on the design and implementation of parallel and cascade topologies in addition to the realization of high-speed FIR filters using FPGAs. An FPGA-based FIR filter's design, implementation, and verification using Verilog HDL are thoroughly analyzed. It is demonstrated that the filter's hardware implementation is effective in terms of clock frequency, utilization of resources, and latency. the architectures are also contrasted, and their benefits and shortcomings are discussed. the parallel architecture is better suitable for high-speed FIR filters than the cascade architecture, according to implementation findings on a Xilinx Spartan-3E FPGA and a VIRTEX FPGA.
In order to improve the classification function and operation performance of human resources, a new big data parallel classification system is designed. the parallel processor is installed to optimize the analog-to-di...
详细信息
ISBN:
(纸本)9783030945510;9783030945503
In order to improve the classification function and operation performance of human resources, a new big data parallel classification system is designed. the parallel processor is installed to optimize the analog-to-digital converter, human resource data storage and wireless communication network. this paper constructs a social information cognitive model, under which human resource data can be obtained in real time, and preprocessed by data cleaning, Chinese word segmentation and stop word elimination. Human resource data features are extracted, and the similarity between the extracted data features and standard data features is calculated to realize the parallel classification function of human resource big data. through the system test experiment, the conclusion is drawn: compared withthe traditional classification system, the recall rate and accuracy rate of the design system are increased by 5.5% and 3.5% respectively, and it has more advantages in classification speed.
the exponential evolution of big data with its increasing volumes, especially when it comes to videos from smart devices and video sites, has become a real challenge to video analysis tasks algorithms. processing and ...
详细信息
暂无评论