IEEE关于网络上信号和信息处理的事务发表了高质量的论文，这些论文将经典的向量空间(例如时间和空间)上定义的信号处理概念扩展到网络上定义的信号和信息(数据)处理，这些数据可能是动态变化的。在网络上的信号处理中，网络的拓扑结构可以定义数据中的结构关系，也可以约束数据的处理。主题包括用于过滤、检测、估计、适应和学习的分布式算法、模型选择、数据融合、信息在此类网络上的扩散或演化，以及分布式信号处理的应用。
The IEEE Transactions on Signal and Information Processing over Networks publishes high-quality papers that extend the classical notions of processing of signals defined over vector spaces (e.g. time and space) to processing of signals and information (data) defined over networks, potentially dynamically varying. In signal processing over networks, the topology of the network may define structural relationships in the data, or may constrain processing of the data. Topics include distributed algorithms for filtering, detection, estimation, adaptation and learning, model selection, data fusion, and diffusion or evolution of information over such networks, and applications of distributed signal processing.