The same two-stage decoder as above. However, when transforming the symbols prior to Viterbi decoding, the amplitude information is ignored and only the phase of the received symbol is employed in the metric computation stage.
This getting started exercise will guide you through the step-by-step process of transforming a MATLAB floating-point model into a hardware module that can be implemented in silicon (FPGA or ASIC). The design is a general purpose FIR filter taken from the AccelDSP Examples directory.
為解決直流逆變交流的問(wèn)題，有效地利用能源，讓電源輸出最大功率，設(shè)計(jì)了高性能的基于IR2101最大功率跟蹤逆變器，并以SPMC75F2413A單片機(jī)作為主控制器。高電壓、高速功率的MOSFET或IGBT驅(qū)動(dòng)器IR2101采用高度集成的電平轉(zhuǎn)換技術(shù)，同時(shí)上管采用外部自舉電容上電，能夠穩(wěn)定高效地驅(qū)動(dòng)MOS管。該逆變器可以實(shí)現(xiàn)DC/AC的轉(zhuǎn)換，最大功率點(diǎn)的跟蹤等功能。實(shí)際測(cè)試結(jié)果表明，該逆變器系統(tǒng)具有跟蹤能力強(qiáng)，穩(wěn)定性高，反應(yīng)靈敏等特點(diǎn)，該逆變器不僅可應(yīng)用于普通的電源逆變系統(tǒng)，而且可應(yīng)用于光伏并網(wǎng)發(fā)電的逆變系統(tǒng)，具有廣泛的市場(chǎng)前景。
Abstract:
To solve the problem of DC-AC inverter， and to utilize solar energy more efficiently， the design of maximum power point tracking inverter based on IR2101 was achieved with a high-performance， which can make the system output power maximum. SPMC75F2413A was adopted as main controller. IR2101 is a high voltage， high speed power MOSFET and IGBT driver. It adopted highly integrated voltage level transforming technology， and an external bootstrap capacitor was used， which could drive MOS tube efficiently and stably. Many functions are achieved in the system， such as DC/AC conversion， maximun power point tracking， etc. The actual test result shows that the inverter system has characteristics of strong tracking ability， high stability and reacting quickly. The design can not only be used in ordinary power inverter system， but also be used in photovoltaic power inverter system. The design has certain marketing prospects
This book presents an insightful view of XML that places this emerging technology in the context of the ongoing Web revolution. Written for business and technical professionals, this book revals the true value of XML for distributed information systems. It explains how XML is transforming the way organizations manage data and build software systems details the opportunities the language offers for organizatoins that understand tis significance and potential impact and explains how XML and Web services reflect a fundamental shift in software construction-from monolithic applications to software based on the composition of simple parts.
從s60平臺(tái)移植到UIQ平臺(tái)的例子代碼：In this code we shall consider taking a simple HelloWorld GUI application written for the Nokia’s Series 60 reference design and transforming it into a HelloWorld example for the UIQ reference design.
The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feature-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented.
In computer vision, sets of data acquired by sampling the same scene or object at different times, or from different perspectives, will be in different coordinate systems. Image registration is the process of transforming the different sets of data into one coordinate system. Registration is necessary in order to be able to compare or integrate the data obtained from different measurements. Image registration is the process of transforming the different sets of data into one coordinate system. To be precise it involves finding transformations that relate spatial information conveyed in one image to that in another or in physical space. Image registration is performed on a series of at least two images, where one of these images is the reference image to which all the others will be registered. The other images are referred to as target images.
