scispace - formally typeset
Search or ask a question
Institution

Hewlett-Packard

CompanyPalo Alto, California, United States
About: Hewlett-Packard is a company organization based out in Palo Alto, California, United States. It is known for research contribution in the topics: Signal & Substrate (printing). The organization has 34663 authors who have published 59808 publications receiving 1467218 citations. The organization is also known as: Hewlett Packard & Hewlett-Packard Company.


Papers
More filters
Journal ArticleDOI
TL;DR: In this paper, the authors present a new approach to scalable quantum computing called a "qubus computer" which realizes qubit measurement and quantum gates through interacting qubits with a quantum communication bus mode.
Abstract: We present here a new approach to scalable quantum computing—a 'qubus computer'—which realizes qubit measurement and quantum gates through interacting qubits with a quantum communication bus mode. The qubits could be 'static' matter qubits or 'flying' optical qubits, but the scheme we focus on here is particularly suited to matter qubits. There is no requirement for direct interaction between the qubits. Universal two-qubit quantum gates may be effected by schemes which involve measurement of the bus mode, or by schemes where the bus disentangles automatically and no measurement is needed. In effect, the approach integrates together qubit degrees of freedom for computation with quantum continuous variables for communication and interaction.

195 citations

Proceedings ArticleDOI
07 Oct 2001
TL;DR: A simple derivation is presented to show that RS generates the minimum mean-squared error (MMSE) estimate of the high- resolution image, given the low-resolution image.
Abstract: We introduce a new approach to optimal image scaling called resolution synthesis (RS). In RS, the pixel being interpolated is first classified in the context of a window of neighboring pixels; and then the corresponding high-resolution pixels are obtained by filtering with coefficients that depend upon the classification. RS is based on a stochastic model explicitly reflecting the fact that pixels falls into different classes such as edges of different orientation and smooth textures. We present a simple derivation to show that RS generates the minimum mean-squared error (MMSE) estimate of the high-resolution image, given the low-resolution image. The parameters that specify the stochastic model must be estimated beforehand in a training procedure that we have formulated as an instance of the well-known expectation-maximization (EM) algorithm. We demonstrate that the model parameters generated during the training may be used to obtain superior results even for input images that were not used during the training.

195 citations

Journal ArticleDOI
TL;DR: This work proposes an alternative compressed domain-based approach that computes motion vectors for the downscaled (N/ 2xN/2) video sequence directly from the original motion vectors from the N/spl times/N video sequence, and discovers that the scheme produces better results by weighting the originalmotion vectors adaptively.
Abstract: Digital video is becoming widely available in compressed form, such as a motion JPEG or MPEG coded bitstream. In applications such as video browsing or picture-in-picture, or in transcoding for a lower bit rate, there is a need to downscale the video prior to its transmission. In such instances, the conventional approach to generating a downscaled video bitstream at the video server would be to first decompress the video, perform the downscaling operation in the pixel domain, and then recompress it as, say, an MPEG, bitstream for efficient delivery. This process is computationally expensive due to the motion-estimation process needed during the recompression phase. We propose an alternative compressed domain-based approach that computes motion vectors for the downscaled (N/2xN/2) video sequence directly from the original motion vectors for the N/spl times/N video sequence. We further discover that the scheme produces better results by weighting the original motion vectors adaptively. The proposed approach can lead to significant computational savings compared to the conventional spatial (pixel) domain approach. The proposed approach is useful for video severs that provide quality of service in real time for heterogeneous clients.

195 citations

Patent
13 Sep 2001
TL;DR: In this paper, methods for enabling an enterprise to run as a zero-latency enterprise (ZLE) and for running an enterprise as a ZLE are provided for enabling the enterprise to integrate its services, applications and data in real time.
Abstract: Methods are provided for enabling an enterprise to run as a zero latency enterprise (ZLE) and for running an enterprise as a ZLE. Such methods allow the enterprise to integrate its services, applications and data in real time. Namely, an enterprise equipped to run as a ZLE is capable of integrating, in real time, its enterprise-wide data, applications, business transactions, operations and values. Consequently, an enterprise conducting its business as a ZLE exhibits superior management of its resources, operations and customer care.

194 citations

Journal ArticleDOI
B.M. Oliver1
01 May 1965
TL;DR: In this paper, the theory of black body radiation, thermal noise, and quantum noise from a few basic physical principles was developed and applied to certain areas such as antenna theory and ideal receivers.
Abstract: One purpose of this article is to develop the theory of black body radiation, thermal noise, and quantum noise from a few basic physical principles. A second purpose is to show how these results apply to certain areas such as antenna theory and ideal receivers. It is hoped that having this related material collected and presented in the language of the electronics engineer will be of tutorial value.

194 citations


Authors

Showing all 34676 results

NameH-indexPapersCitations
Andrew White1491494113874
Stephen R. Forrest1481041111816
Rafi Ahmed14663393190
Leonidas J. Guibas12469179200
Chenming Hu119129657264
Robert E. Tarjan11440067305
Hong-Jiang Zhang11246149068
Ching-Ping Wong106112842835
Guillermo Sapiro10466770128
James R. Heath10342558548
Arun Majumdar10245952464
Luca Benini101145347862
R. Stanley Williams10060546448
David M. Blei98378111547
Wei-Ying Ma9746440914
Network Information
Related Institutions (5)
IBM
253.9K papers, 7.4M citations

94% related

Samsung
163.6K papers, 2M citations

90% related

Carnegie Mellon University
104.3K papers, 5.9M citations

90% related

Microsoft
86.9K papers, 4.1M citations

90% related

Bell Labs
59.8K papers, 3.1M citations

89% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
202223
2021240
20201,028
20191,269
2018964