The Dirichlet process is an important fundamental object in nonparametric Bayesian modelling, applied to a wide range of problems in machine learning, statistics, and bioinformatics, among other fields. This flexible stochastic process models rich data structures with unknown or evolving number of clusters. It is a valuable tool for encoding the true complexity of real-world data in computer models. Our results show that the Dirichlet process improves, both in distribution density and in signal-to-noise ratio, with larger sample size; achieves slow decay rate to its base distribution; has improved convergence and stability; and thrives with a Gaussian base distribution, which is much better than the Gamma distribution. The performance depends greatly on the choice of base distribution. The higher the value of α (a concentration parameter), the better the clustering and noise suppression. The distributional behavior of data can be approximated rigorously by the biorthogonal wavelet analysis. Since the Dirichlet process is an interesting object of observation, we computed it for a few wavelet bases and among them, we found that the Cohen-Daubechies-Feauveau (CDF) basis is the one that captures the Dirichlet process most accurately. Our results may be useful in applying the Dirichlet process to real-world experimental data and in developing Bayesian non-parametric methods.
The Research topic seeks to analyze the "political risk and its component Terrorism Index," which consists of five indicators index, a number of terrorist operations, and the number of dead and wounded, and the size of the physical losses, based search sub-index analysis of material losses for the index terrorism and its impact on the indicators listed on the Iraq Stock Exchange Finance. As for the practical side, it has been use style gradient unrestricted and link the sample represented by ten banks listed on the Iraq Stock Exchange. was Statement the correlation and interaction of variables of the studySearch results produced that the volume of material losses is the most important indicator in the influential force and it explain a v
... Show MoreThe Field Programmable Gate Array (FPGA) approach is the most recent category, which takes the place in the implementation of most of the Digital Signal Processing (DSP) applications. It had proved the capability to handle such problems and supports all the necessary needs like scalability, speed, size, cost, and efficiency.
In this paper a new proposed circuit design is implemented for the evaluation of the coefficients of the two-dimensional Wavelet Transform (WT) and Wavelet Packet Transform (WPT) using FPGA is provided.
In this implementation the evaluations of the WT & WPT coefficients are depending upon filter tree decomposition using the 2-D discrete convolution algorithm. This implementation w
... Show MoreFinancial markets play an important role in the economy, as it contributes to the financial and economic system of the state stability, as it reduces the adoption of the companies on the loans granted by the banks, as financial markets contribute to attracting and channeling savings to small savers who will be able to buy a number of shares proportional to their savings, It also provides them the place of exchange, and play technology and information systems an important role in facilitating exchanges and increased market activity, in this research touched on the importance of information technology in effect on the activity of the financial markets. Research is divided into three demands of the first concept of eating and the importance
... Show MoreABSTRACT this paper extends the literature on the elements and effect of financial literacy by investigating the elements of financial literacy and the impact of financial literacy on financial inclusion and savings. This research confirms the results of researches of other economies but exposes some dissimilarities as well. The principal factors of financial literacy are discovered to be government efficiency, educational level, income, economic performance and infrastructure. Both education levels and financial literacy are found to be meaningfully and positively linked to financial inclusion and savings in G20 economies
Undoubtedly, Road Traffic Accidents (RTAs) are a major dilemma in term of mortality and morbidity facing the road users as well as the traffic and road authorities. Since 2002, the population in Iraq has increased by 49 percent and the number of vehicles by three folds. Consequently, these increases were unfortunately combined with rising the RTAs number, mortality and morbidity. Alongside the humanitarian tragedies, every year, there are considerable economic losses in Iraq lost due to the epidemic of RTAs. Given the necessity of understanding the contributory factors related to RTAs for the implementation by traffic and road authorities to improve the road safety, the necessity have been a rise for
... Show MoreUndoubtedly, Road Traffic Accidents (RTAs) are a major dilemma in term of mortality and morbidity facing the road users as well as the traffic and road authorities. Since 2002, the population in Iraq has increased by 49 percent and the number of vehicles by three folds. Consequently, these increases were unfortunately combined with rising the RTAs number, mortality and morbidity. Alongside the humanitarian tragedies, every year, there are considerable economic losses in Iraq lost due to the epidemic of RTAs. Given the necessity of understanding the contributory factors related to RTAs for the implementation by traffic and road authorities to improve the road safety, the necessity have been a rise for this research which focuses into
... Show MoreThis search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com
... Show MoreEmbedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.
This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as
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