Proceedings of the IEEE

Big Data applications are typically associated with systems involving large numbers of users, massive complex software systems, and large-scale heterogeneous computing and storage architectures. The construction of such systems involves many distributed design choices. The end products (e.g., recommendation systems, medical analysis tools, real-time game engines, speech recognizers) thus involve m... View full abstract»

The Internet has led to the creation of a digital society, where (almost) everything is connected and is accessible from anywhere. However, despite their widespread adoption, traditional IP networks are complex and very hard to manage. It is both difficult to configure the network according to predefined policies, and to reconfigure it to respond to faults, load, and changes. To make matters even ... View full abstract»

Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters, with minimal preprocessing. This paper rev... View full abstract»

Deep neural networks (DNNs) are currently widely used for many artificial intelligence (AI) applications including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Accordingly, techniques that enable efficient processing of DNNs to improve energy efficiency and throughput without... View full abstract»

In this paper, we provide an introduction to machine learning tasks that address important problems in genomic medicine. One of the goals of genomic medicine is to determine how variations in the DNA of individuals can affect the risk of different diseases, and to find causal explanations so that targeted therapies can be designed. Here we focus on how machine learning can help to model the relati... View full abstract»

Initially developed for gaming and 3-D rendering, graphics processing units (GPUs) were recognized to be a good fit to accelerate deep learning training. Its simple mathematical structure can easily be parallelized and can therefore take advantage of GPUs in a natural way. Further progress in compute efficiency for deep learning training can be made by exploiting the more random and approximate na... View full abstract»

Wind power now represents a major and growing source of renewable energy. Large wind turbines (with capacities of up to 6-8 MW) are widely installed in power distribution networks. Increasing numbers of onshore and offshore wind farms, acting as power plants, are connected directly to power transmission networks at the scale of hundreds of megawatts. As its level of grid penetration has begun to i... View full abstract»

Earth orbiting satellites come in a wide range of shapes and sizes to meet a diverse variety of uses and applications. Large satellites with masses over 1000 kg support high-resolution remote sensing of the Earth, high bandwidth communications services, and world-class scientific studies but take lengthy developments and are costly to build and launch. The advent of commercially available, high-vo... View full abstract»

Solid-state drives (SSDs) based on NAND flash are making deep inroads into data centers as well as the consumer market. In 2016, manufacturers shipped more than 130 million units totaling around 50 Exabytes of storage capacity. As the amount of data stored on solid state drives keeps increasing, it is important to understand the reliability characteristics of these devices. For a long time, our kn... View full abstract»

In recent years, the negative capacitance effect in ferroelectric (FE) materials has attracted significant attention from many researchers around the world. The negative capacitance effect promises to reduce the voltage requirement in conventional complementary metal-oxide-semiconductor transistors below what is otherwise believed to be the Boltzmann limit. In this paper, our objective is to discu... View full abstract»

This paper describes the use of physical unclonable functions (PUFs) in low-cost authentication and key generation applications. First, it motivates the use of PUFs versus conventional secure nonvolatile memories and defines the two primary PUF types: “strong PUFs” and “weak PUFs.” It describes strong PUF implementations and their use for low-cost authentication. After this description, the paper ... View full abstract»

Hardware/software codesign investigates the concurrent design of hardware and software components of complex electronic systems. It tries to exploit the synergy of hardware and software with the goal to optimize and/or satisfy design constraints such as cost, performance, and power of the final product. At the same time, it targets to reduce the time-to-market frame considerably. This paper presen... View full abstract»

Antenna is one of the key components onboard small satellites as its design determines the performance of all the wireless systems including telemetry, tracking and control, high-speed data downlink, navigation, intersatellite communications, intrasatellite communications, wireless power transfer, radars and sensors, etc. This paper presents a review of recent development in advanced antennas for ... View full abstract»

Braindrop is the first neuromorphic system designed to be programmed at a high level of abstraction. Previous neuromorphic systems were programmed at the neurosynaptic level and required expert knowledge of the hardware to use. In stark contrast, Braindrop's computations are specified as coupled nonlinear dynamical systems and synthesized to the hardware by an automated procedure. This procedure n... View full abstract»

Thin-film electronics in its myriad forms has underpinned much of the technological innovation in the fields of displays, sensors, and energy conversion over the past four decades. This technology also forms the basis of flexible electronics. Here we review the current status of flexible electronics and attempt to predict the future promise of these pervading technologies in healthcare, environmen... View full abstract»

Advanced energy storage has been a key enabling technology for the portable electronics explosion. The lithium and Ni-MeH battery technologies are less than 40 years old and have taken over the electronics industry and are on the same track for the transportation industry and the utility grid. In this review, energy storage from the gigawatt pumped hydro systems to the smallest watt-hour battery a... View full abstract»

Millimeter-wave (mmW) frequencies between 30 and 300 GHz are a new frontier for cellular communication that offers the promise of orders of magnitude greater bandwidths combined with further gains via beamforming and spatial multiplexing from multielement antenna arrays. This paper surveys measurements and capacity studies to assess this technology with a focus on small cell deployments in urban e... View full abstract»

Due to the broadcast nature of radio propagation, the wireless air interface is open and accessible to both authorized and illegitimate users. This completely differs from a wired network, where communicating devices are physically connected through cables and a node without direct association is unable to access the network for illicit activities. The open communications environment makes wireles... View full abstract»

Relational machine learning studies methods for the statistical analysis of relational, or graph-structured, data. In this paper, we provide a review of how such statistical models can be “trained” on large knowledge graphs, and then used to predict new facts about the world (which is equivalent to predicting new edges in the graph). In particular, we discuss two fundamentally different kinds of s... View full abstract»

The world's appetite for analyzing massive amounts of structured and unstructured data has grown dramatically. The computational demands of these abundant-data applications, such as deep learning, far exceed the capabilities of today's computing systems and are unlikely to be met with isolated improvements in transistor or memory technologies, or integrated circuit architectures alone. To achieve ... View full abstract»

Smart grids are electric networks that employ advanced monitoring, control, and communication technologies to deliver reliable and secure energy supply, enhance operation efficiency for generators and distributors, and provide flexible choices for prosumers. Smart grids are a combination of complex physical network systems and cyber systems that face many technological challenges. In this paper, w... View full abstract»

The silicon nitride (Si3N4) planar waveguide platform has enabled a broad class of low-loss planar-integrated devices and chip-scale solutions that benefit from transparency over a wide wavelength range (400-2350 nm) and fabrication using wafer-scale processes. As a complimentary platform to silicon-on-insulator (SOI) and III-V photonics, Si3N4waveguide ... View full abstract»

Inductive power transfer (IPT) was an engineering curiosity less than 30 years ago, but, at that time, it has grown to be an important technology in a variety of applications. The paper looks at the background to IPT and how its development was based on sound engineering principles leading on to factory automation and growing to a $1 billion industry in the process. Since then applications for the... View full abstract»

Driven by the rapid escalation of the wireless capacity requirements imposed by advanced multimedia applications (e.g., ultrahigh-definition video, virtual reality, etc.), as well as the dramatically increasing demand for user access required for the Internet of Things (IoT), the fifth-generation (5G) networks face challenges in terms of supporting large-scale heterogeneous data traffic. Nonorthog... View full abstract»

This paper provides a theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees. An overview of basic concepts of information consensus in networks and methods of convergence and performance analys... View full abstract»