The organization of behavior: A neuropsychological theory

International Journal of Computer and Applications

There has been a great deal of material in the area of discrete-time transforms that has been published in recent years. This book does an excellent job of presenting important aspects of such material in a clear manner. The book has 11 chapters and a very useful appendix. Seven of these chapters are essentially devoted to the Fourier series/transform, discrete Fourier transform, fast Fourier transform (FFT), and applications of the FFT in the area of spectral estimation. Chapters 8 through 10 deal with many other discrete-time transforms and algorithms to compute them. Of these transforms, the KarhunenLoeve, the discrete cosine, and the Walsh-Hadamard transform are perhaps the most well-known. A lucid discussion of number theoretic transforms i5 presented in Chapter 11. This reviewer feels that the authors have done a fine job of compiling the pertinent material and presenting it in a concise and clear manner. There are a number of problems at the end of each chapter, an appreciable number of which are challenging. The authors have included a comprehensive set of references at the end of the book. In brief, this book is a valuable contribution to the general areas of signal processing and communications. It can be used for a graduate level course in perhaps two ways. One would be to cover the first seven chapters in great detail. The other would be to cover the whole book by focussing on different topics in a selective manner. This book  by  Elliott  and Rao  is extremely  useful to researchers/engineers who are working  in the areas of signal processing and communications. It i s also an excellent reference book, and hence a valuable addition to one’s library

http://ieeexplore.ieee.org/iel5/5/31347/01457444.pdf

Multirate digital signal processing

http://ieeexplore.ieee.org/iel5/5/31324/01456901.pdf

Microelectronic circuits

digital signal processing a computer based approach is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the digital signal processing a computer based approach is universally compatible with any devices to read.

Digital Signal Processing A Computer Based Approach

Breast cancer histology images classification: Training from scratch or transfer learning?

Automatic multi-classification of breast cancer histopathological images has remained one of the top-priority research areas in the field of biomedical informatics, due to the great clinical significance of multi-classification in providing diagnosis and prognosis of breast cancer. In this work, two machine learning approaches are thoroughly explored and compared for the task of automatic magnification-dependent multi-classification on a balanced BreakHis dataset for the detection of breast cancer. The first approach is based on handcrafted features which are extracted using Hu moment, color histogram, and Haralick textures. The extracted features are then utilized to train the conventional classifiers, while the second approach is based on transfer learning where the pre-existing networks (VGG16, VGG19, and ResNet50) are utilized as feature extractor and as a baseline model. The results reveal that the use of pre-trained networks as feature extractor exhibited superior performance in contrast to baseline approach and handcrafted approach for all the magnifications. Moreover, it has been observed that the augmentation plays a pivotal role in further enhancing the classification accuracy. In this context, the VGG16 network with linear SVM provides the highest accuracy that is computed in two forms, (a) patch-based accuracies (93.97% for 40×, 92.92% for 100×, 91.23% for 200×, and 91.79% for 400×); (b) patient-based accuracies (93.25% for 40×, 91.87% for 100×, 91.5% for 200×, and 92.31% for 400×) for the classification of magnification-dependent histopathological images. Additionally, "Fibro-adenoma" (benign) and "Mucous Carcinoma" (malignant) classes have been found to be the most complex classes for the entire magnification factors.

https://link.springer.com/content/pdf/10.1007/s10278-019-00307-y.pdf

Conventional Machine Learning and Deep Learning Approach for Multi-Classification of Breast Cancer Histopathology Images—a Comparative Insight

In this paper, Power Spectral Estimation (PSE) scheme for variable data length using Rectangular, Blackman, Hanning, Bartlett and Hamming window with Welch Method. Welch method includes the periodogram having advantage of possible implementation using the Fast Fourier Transform (FFT). This method gives good resolution when optimal selection of data length samples is done. The PSE based on both Rectangular as well as Hamming window has been designed and simulated using MATLAB. It can be observed that the Rectangular and Hamming give better results than other windows like Bartlett, Hanning and Blackman window.

Analysis of Power Spectrum Estimation Using Welch Method for Various Window Techniques

The perovskite solar cells (PSCs) which are Pb free have gained much research enthusiasm because of the toxic nature of the lead-based halide perovskite. MASnI3 is a feasible contrasting option to MAPbX3, in light of the fact that it has broader visible absorption spectrum range and smaller band gap value of 1.3 eV than MAPbI3. The advance of fabricating Sn-based PSCs with great strength has animated the investigations of these MASnI3-based solar cells enormously. In this paper, planar heterojunction design of Sn-based iodide PSC is proposed. The copper antimony sulfide (CuSbS2) which is inorganic material is used for the very first time as hole transport layer (HTL) in conjunction with the MASnI3 active layer in this design because of its inherent features (high abundance and high open-circuit voltage) as compared to the unstable and costly Spiro-MeOTAD. With integration of CuSbS2 as a HTL in the design, the outcomes are competent enough with Jsc of 31.7 mA/cm2, Voc of 0.936 V, FF of 81.1% and PCE of 24.1%. The outcomes demonstrate that the Pb-free MASnI3 PSC is a future perspective to the photovoltaic community in terms of environment friendly nature and yielding comparative high efficiency as of lead-based halide perovskite cell.

Device simulation of lead-free MASnI3 solar cell with CuSbS2 (copper antimony sulfide)

Leakage power has become a serious concern in nanometer CMOS technologies. In the past, the dynamic power has dominated the total power dissipation of CMOS devices. However, with the continuous trend of technology scaling, leakage power is becoming a main contributor to power consumption. In the past many methods had been proposed for leakage power reduction like forced stack, sleepy stack, sleepy keeper, dual sleep approach etc. using techniques like transistor sizing, multi-Vth, dual-Vth, stacking transistors etc. In this paper, new methods have been proposed for the leakage power reduction in 90nm technology. The proposed methods will be compared with the previous existing leakage reduction techniques. The result is simulated using Microwind 3.1 in 90nm CMOS technology at room temperature.

/pdf/leakage-power-reduction-in-cmos-vlsi-circuits-215tqwntpn.pdf

Rajesh Mehra

Papers

Breast cancer histology images classification: Training from scratch or transfer learning?

Conventional Machine Learning and Deep Learning Approach for Multi-Classification of Breast Cancer Histopathology Images—a Comparative Insight

Analysis of Power Spectrum Estimation Using Welch Method for Various Window Techniques

Device simulation of lead-free MASnI3 solar cell with CuSbS2 (copper antimony sulfide)

Leakage Power Reduction in CMOS VLSI Circuits