IEEE關(guān)于網(wǎng)絡(luò)上信號(hào)和信息處理的事務(wù)發(fā)表了高質(zhì)量的論文，這些論文將經(jīng)典的向量空間(例如時(shí)間和空間)上定義的信號(hào)處理概念擴(kuò)展到網(wǎng)絡(luò)上定義的信號(hào)和信息(數(shù)據(jù))處理，這些數(shù)據(jù)可能是動(dòng)態(tài)變化的。在網(wǎng)絡(luò)上的信號(hào)處理中，網(wǎng)絡(luò)的拓?fù)浣Y(jié)構(gòu)可以定義數(shù)據(jù)中的結(jié)構(gòu)關(guān)系，也可以約束數(shù)據(jù)的處理。主題包括用于過濾、檢測(cè)、估計(jì)、適應(yīng)和學(xué)習(xí)的分布式算法、模型選擇、數(shù)據(jù)融合、信息在此類網(wǎng)絡(luò)上的擴(kuò)散或演化，以及分布式信號(hào)處理的應(yīng)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.