A New Approach to Adaptive Signal Processing

A unified linear algebraic approach to adaptive signal processing (ASP) is presented. Starting from just Ax=b, key ASP algorithms are derived in a simple, systematic, and integrated manner without requiring any background knowledge to the field. Algorithms covered are Steepest Descent, LMS, Normalized LMS, Kaczmarz, Affine Projection, RLS, Kalman filter, and MMSE/Least Square Wiener filters. By following this approach, readers will discover a synthesis; they will learn that one and only one equation is involved in all these algorithms. They will also learn that this one equation forms the basis of more advanced algorithms like reduced rank adaptive filters, extended Kalman filter, particle filters, multigrid methods, preconditioning methods, Krylov subspace methods and conjugate gradients. This will enable them to enter many sophisticated realms of modern research and development. Eventually, this one equation will not only become their passport to ASP but also to many highly specialized areas of computational science and engineering

Adaptive System Identification using Markov Chain Monte Carlo

One of the major problems in adaptive filtering is the problem of system identification. It has been studied extensively due to its immense practical importance in a variety of fields. The underlying goal is to identify the impulse response of an unknown system. This is accomplished by placing a known system in parallel and feeding both systems with the same input. Due to initial disparity in their impulse responses, an error is generated between their outputs. This error is set to tune the impulse response of known system in a way that every change in impulse response reduces the magnitude of prospective error. This process is repeated until the error becomes negligible and the responses of both systems match. To specifically minimize the error, numerous adaptive algorithms are available. They are noteworthy either for their low computational complexity or high convergence speed. Recently, a method, known as Markov Chain Monte Carlo (MCMC), has gained much attention due to its remarkably low computational complexity. But despite this colossal advantage, properties of MCMC method have not been investigated for adaptive system identification problem. This article bridges this gap by providing a complete treatment of MCMC method in the aforementioned context

Learning style preference and critical thinking perception among engineering students

Engineering education plays a vital role towards modernization of world. Therefore, engineering students need to be nurture with multiple skills like learning preferences and critical thinking skills. This study has been conducted to identify the learning style preferences and critical thinking perception of the engineering students from three programs electrical engineering, mechanical engineering and civil engineering at Universiti Tun Hussein Onn Malaysia (UTHM), Johor. Survey research design was applied in this study. The quantitative data was collected by two questionnaires Index of Learning Styles (ILS) that is based on Felder-Silverman Learning Style Model (FSLSM) and Critical Thinking Skills (CTS) questionnaire which consists of analysis, evaluation, induction and deduction in terms of problem solving and decision making. A total of 315 final year engineering students were participated in this study. Data was analyzed in descriptive and inferential statistics involving tests Analysis of Variance (ANOVA), Pearson Correlation and linear regression. The study discovered that engineering students are preferred to be visual learners (83.80%). Visual learning style denotes FSLSM input dimension and visual learners learn best by diagrams, charts, maps and graphical presentations. This study also found that engineering students possess critical thinking perception in all dimensions. However, there is no statistical significant difference of learning style found among engineering programs as “p” value found 0.357. Whereas, there is statistical significant critical thinking difference found among engineering programs as “p” value found 0.006. Lastly, findings revealed that there is no significant relationship found between learning styles and critical thinking skills. The study findings suggested that providing preferred learning style (visual learning style) in classroom will enhance students’ academic achievement and increase their cognitive level. This study might serve as a guideline for educators to facilitate learners to enhance their learning and thinking for better outcomes in academia as well as in workplace

Role of agriculture in economic growth of Pakistan

This research based on the role of agriculture in the economic growth of Pakistan. Secondary data has been collected from the year 1980-2010 from the government authentic websites. For this purpose simple regression applied to identify the significance relationship of agricultural sub-sectors with GDP. Results suggested that there is the significance role of agriculture sub-sectors towards the economic growth only forestry showed insignificant relationship with GDP. Another objective is based on to know the contribution of each sub-sector over the aggregate agriculture amount. Result suggest that crops and livestock’s total contribute 91% combined in the aggregate agriculture sector that represent significance contribution for the performance regarding in this sector while fisheries and forestry have minimal contribution because of many reasons, major reasons involved low investment intensity in this sector, insufficient facilities, untrained and unskillful labor force engaged with it.Economic growth, major crops, minor crops, Livestock, forestry, fisheries, Gross Domestic Product (GDP)

More on Comparison Between First Geometric-Arithmetic Index and Atom-Bond Connectivity Index

The first geometric-arithmetic (GA) index and atom-bond connectivity (ABC) index are molecular structure descriptors which play a significant role in quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR) studies. Das and Trinajsti\'{c} [\textit{Chem. Phys. Lett.} \textbf{497} (2010) 149-151] showed that $GA$ index is greater than $ABC$ index for all those graphs (except $K_{1,4}$ and $T^{*}$, see Figure 1) in which the difference between maximum and minimum degree is less than or equal to 3. In this note, it is proved that $GA$ index is greater than $ABC$ index for line graphs of molecular graphs, for general graphs in which the difference between maximum and minimum degree is less than or equal to $(2\delta-1)^{2}$ (where $\delta$ is the minimum degree and $\delta\geq2$) and for some families of trees. Thereby, a partial solution to an open problem proposed by Das and Trinajsti\'{c} is given.Comment: 10 pages, 2 tables, 1 figure, revised versio