Research Instrumentation

该机构基础设施奖授予了东北大学，用于开发连接计算机科学学院和工程学院数字信号处理小组的强大工作站和服务器的网络环境。基础设施支持许多领域的研究，其中许多是合作性的。用于移动通信的CDMA涉及几个活动，包括设计用于最小化通信干扰的伪随机序列，设计具有栅格编码的有效CPM信号，以及确定多用户移动信道容量的基本限制。神经网络的研究涉及神经网络的体系结构和学习算法。通信网络研究包括研究高速局域网和城域网、桥接局域网和分组无线网络中的通信协议。对更多数学主题的研究包括计算代数和编译器正确性的代数模型。数字信号处理的研究涉及到听力、高阶谱、图像处理、自适应信号处理方法、联合源编码理论等方面的研究。对于计算机科学家和电气工程师来说，信号处理是一个天然的合作领域。用数字技术代替模拟技术需要更多地使用计算来解释通信。这项基础设施拨款支持的研究包括如何使本地网络之间和其他网络之间进行良好的通信，开发新算法以消除噪声并优化通信链路的信息承载能力，开发算法以使计算机网络能够像蜂窝电话网络一样工作，在学习、代数和编译器的数学基础上进行更多的理论研究。

This Institutional Infrastructure award to Northeastern University is for the development of a networked environment of powerful workstations and servers linking the College of Computer Science and the Digital Signal Processing group in the College of Engineering. The infrastructure supports research in a number of areas, many of them collaborative. CDMA for mobile communications involves several activities including the design of pseudorandom sequences for minimizing communication interference, the design of efficient CPM signals with trellis coding, and determining the fundamental limits on the capacity of multiple user mobile channels. Research on neural nets involves both architectures for neural nets and learning algorithms. Communication network research involves studying protocols for communications in high speed LANs and MANs, bridging LANs, and packet radio networks. Research on more mathematical topics includes computational algebra and algebraic models for compiler correctness. Digital signal processing research involves studies of hearing, high order spectra, image processing, adaptive signal processing methods, and joint source coding theory. Signal processing is a natural collaborative area for computer scientists and electrical engineers. The replacement of analog techniques by digital techniques requires a much more intensive use of computation in order to interpret communications. The research supported by this infrastructure grant includes work on how to make local networks communications well amongst themselves and other networks, the development of new algorithms to get rid of noise and to optimize the information carrying capacity of communications links, the development of algorithms that will allow networks of computers to work the same way as cellular phone networks, and more theoretical work in studying the mathematical underpinnings of learning, algebra, and compilers.