Implementation of RNS-Based Distributed Arithmetic Discrete Wavelet Transform Architectures Using Field-Programmable Logic

Currently there are design barriers inhibiting the implementation of high-precision digital signal processing (DSP) objects with field programmable logic (FPL) devices. This paper explores overcoming these barriers by fusing together the popular distributed arithmetic (DA) method with the residue number system (RNS) for use in FPL-centric designs. The new design paradigm is studied in the context of a high-performance filter bank and a discrete wavelet transform (DWT). The proposed design paradigm is facilitated by a new RNS accumulator structure based on a carry save adder (CSA). The reported methodology also introduces a polyphase filter structure that results in a reduced look-up table (LUT) budget. The 2C-DA and RNS-DA are compared, in the context of a FPL implementation strategy, using a discrete wavelet transform (DWT) filter bank as a common design theme. The results show that the RNS-DA, compared to a traditional 2C-DA design, enjoys a performance advantage that increases with precision (wordlength).     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

A social interaction system based on cloud computing for mobile video telephony

As the use of smartphones become popular,people heavily depend on smartphone applications to deal with their social activities.For this reason,traditional message texting between mobile applications does not fulfill the versatile requirements of social networking.Many mobile applications use multimodality to deliver multimedia messages including sticker,voice and photo message,video call,and snap movie to enhance the communicative capability.However,without face-to-face interaction,people may fail to detect the other side’s non-verbal social behavior such as fine-grain facial expressions,body movements,or hand gesture.During social interaction,non-verbal behavior conveys information about the involved individuals and help the speakers express their social emotion in an implicit way.It is so important for real-world face-to-face interaction but is often blocked on the mobile telephony.To cope with this problem,we propose an afective computing model to assist the representation of social emotion and then help the progress of social interaction on the mobile telephony.In this model,for the purpose of real-time afective analysis,we delegate the computing loading to the cloud side service and enhance the system’s scalability and availability.The result of this experiment approves the feasibility of our system design for the applications of social intelligent.Also,the system provides a research framework of the social intelligent system on the mobile telephony.     

一种改进编码器角度解算过程的方法与实现

在机械电子一直是一个热门学科,其目的是通过软件控制机械操作来代替机械的哑巴解决方案。DS-25旋转电子编码器能够很好地与机械电子应用相匹配,其输出为两路标准的sine和cosine曲线,通过分析sine和cosine数值来计算编码器所对应的绝对角度位置。通过对DS-25的工作模式分析和实际应用情况提出角度解算的改进方案,该方案利用DS-25工作于粗略模式下测试到的角度值来推算精确模式下的信号周期,结合精确模式下测试到的角度值来计算编码器所对应的绝对角度。摒弃其原有的复杂查表过程进而节省电子表格的存储空间,在降低硬件成本的同时提升了软件灵活性。实验证明,算法的改进能够节省约2KB的存储空间,角度位置误差能控制在1‰以内。     

Stabilizing switching design for switched linear systems: A state-feedback path-wise switching approach

This paper addresses the problem of switching stabilization for discrete-time switched linear systems. Based on the abstraction-aggregation methodology, we propose a state-feedback path-wise switching law, which is a state-feedback concatenation from a finite set of switching paths each defined over a finite time interval. We prove that the set of state-feedback path-wise switching laws is universal in the sense that any stabilizable switched linear system admits a stabilizing switching law in this set. We further develop a computational procedure to calculate a stabilizing switching law in the set.     

Mathematical methods of geoinformatics. III. Fuzzy comparisons and recognition of anomalies in time series

The search for anomalies in time series by methods of fuzzy logic is further explored. The algorithms DRAS and FLARS underlying these methods are further developed in the form of the algorithm FCARS that is completely based on fuzzy comparisons. Parts 1 and 2 were published in Cybernetics and Systems Analysis, No. 2, 2002 and No. 4, 2003. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 3–18, May–June 2008.     

医用电解质分析仪的研制

对医学常规体液检查中5种离子浓度的检测,利用单片机、高精度A/D芯片、实时时钟等,给出了一种切实可行的解决方案,并详细地阐述了系统的软硬件设计。     

电视节目远程录制与点播系统的设计及应用

在当今社会,每天全国卫星电视网传送出近百套电视节目,覆盖了文化、教育、科技、体育等大量有价值的内容,能否让希望保存这些资源的人或由于某些原因无法及时看到并录制自己所关注节目的人方便快捷地获得这些电视资源?电视节目远程录制与点播系统就可以让使用者很容易地获得所需的电视资源,本文将介绍本系统的设计思想和编程技术。     

两种标准信号之间的函数变换

用函数变换的方法解决两种标准信号之间的转换，进而阐述了数学在解决实际问题中的应用。