nils-herrmann/clean_scirepeval huggingface dataset:
Cache array architecture optimization at deep submicron technologies

A cache access time model, PRACTICS (predictor of access and cycle time for cache stack), has been developed to optimize the memory array architecture for the minimum access and cycle times of on-chip memory using circuit models based on Cadence simulations. Lumped RC models have been used to approximate the distributed RC interconnect network in the access time models. Both SRAM and DRAM models have been validated with industrial designs. The limited influences of gate far-out and transistor size on the cache array architecture indicate that interconnect delay is dominant at deep submicron technologies.
Correlated source coding for fusion storage and selective retrieval

Motivated by the sensor network setting, we consider lossless storage of correlated discrete memoryless sources. The underlying tradeoff is between exploitation of inter-source correlation for low rate storage and efficient (low rate) selective retrieval from the fusion storage. We define the problem of shared descriptions (SD) source coding and relate it to the storage and retrieval problem. We present an achievable rate region for the SD problem and use it to characterize the storage vs. retrieval tradeoff
Video coding with optimal inter/intra-mode switching for packet loss resilience

Resilience to packet loss is a critical requirement in predictive video coding for transmission over packet-switched networks, since the prediction loop propagates errors and causes substantial degradation in video quality. This work proposes an algorithm to optimally estimate the overall distortion of decoder frame reconstruction due to quantization, error propagation, and error concealment. The method recursively computes the total decoder distortion at pixel level precision to accurately account for spatial and temporal error propagation. The accuracy of the estimate is demonstrated via simulation results. The estimate is integrated into a rate-distortion (RD)-based framework for optimal switching between intra-coding and inter-coding modes per macroblock. The cost in computational complexity is modest. The framework is further extended to optimally exploit feedback/acknowledgment information from the receiver/network. Simulation results both with and without a feedback channel demonstrate that precise distortion estimation enables the coder to achieve substantial and consistent gains in PSNR over known state-of-the-art RD- and non-RD-based mode switching methods.
Advances in recursive per-pixel estimation of end-to-end distortion for application in H.264

This paper is concerned with open questions and modifications to expand the applicability of the recursive optimal per-pixel estimate (ROPE) of end-to-end distortion, which are particularly relevant to H.264. One open question involves the emergence of cross-correlation terms in the case of sub-pixel prediction or other pixel filtering operations. A new and improved low-complexity approximation is proposed, which accounts for the inter-pixel distance. Another open question involves the commonly ignored effects of rounding and clipping. The cumulative impact of rounding on the distortion estimate is shown to be extensive at low to medium packet-loss rates. Two schemes are proposed for effective rounding and clipping error compensation. Simulation results for H.264 with 1/4-pel prediction show that the revised ROPE maintains low complexity and achieves estimation accuracy that closely matches that of ROPE in the simpler case of full-pixel prediction, where it is optimal.
Effective high frequency regeneration based on sinusoidal modeling for MPEG-4 HE-AAC

A novel approach is proposed for effective high frequency regeneration in audio coding, which is based on a sinusoids plus noise model. It assumes a standard high efficiency advanced audio coding (HE-AAC) encoder, and modifies the decoder to exploit all available information in estimating the model parameters. From the lower band reconstruction of core AAC, frequency parameters of the high band sinusoids are estimated. Side information about spectral energy and the regenerated high band of standard HE-AAC are employed in estimating the magnitude parameters of the high band sinusoids as well as noise model parameters. The gains achieved by the proposed technique, over conventional HE-AAC, are demonstrated by subjective quality tests that were carried out on audio signals with significant harmonics in the high band.
On Optimal Jamming Over an Additive Noise Channel

This paper considers the problem of optimal zero-delay jamming over an additive noise channel. Early work had solved this problem for a Gaussian source and a Gaussian channel. Building on a sequence of recent results on conditions for linearity of optimal estimation, and of optimal mappings in source-channel coding, we derive the saddle-point solution to the jamming problem for general sources and channels, without recourse to Gaussianness assumptions. We show that linearity conditions play a pivotal role in jamming, in the sense that the optimal jamming strategy is to effectively force both the transmitter and the receiver to default to linear mappings, i.e., the jammer ensures, whenever possible, that the transmitter and the receiver cannot benefit from non-linear strategies. This result is shown to subsume the known result for Gaussian source and channel. We analyze conditions and general settings where such unbeatable strategy can indeed be achieved by the jammer. Moreover, we provide a procedure to approximate optimal jamming in the remaining (source-channel) cases where the jammer cannot impose linearity on the transmitter and the receiver.
Zero-error source-channel coding with source side information at the decoder

This paper describes the zero-error source-channel coding with source side information at the decoder. To analyze the zero-error scenario, we define the following graphs: the source confusability graph G/sub u/ and channel characteristic graph G/sub x/. We can always find a code from a source graph to its complement. Separate source and channel coding corresponds to first mapping from the source alphabet to an index set and then mapping from the index set to the channel alphabet. The size of the smallest index set that allows a zero-error source code is the chromatic number of G/sub u/, /spl chi/(G/sub u/). The largest index set from which we can map to the channel alphabet is the stability number of G/sub x/, /spl alpha/(G/sub x/).
Die-on-wafer and wafer-level 3D integration for millimeter-wave smart antenna transceivers

A three-dimensional (3D) IC technology platform for high-performance, heterogeneous integration of silicon ICs for mm-wave smart antenna transceivers is presented. The platform uses dielectric adhesive bonding of fully-processed wafer-to-wafer aligned ICs, followed by a three-step thinning process and copper damascene patterning to form inter-wafer interconnects. A low noise amplifier (LNA), power amplifier (PA), and an analog-to-digital converter (ADC) are designed in RF-enhanced SiGe BiCMOS process to operate in the 24 GHz ISM band These critical design blocks serve as a step towards the realization of a complete system integrated with I/O matching networks, switches, antennas, and digital processing in a 3D configuration
Estimation-Theoretic Delayed Decoding of Predictively Encoded Video Sequences

Current video coding schemes employ motion compensation to exploit the fact that the signal forms an auto-regressive process along the motion trajectory, and remove temporal redundancies with prior reconstructed samples via prediction. However, the decoder may, in principle, also exploit correlations with received encoding information of future frames. In contrast to current decoders that reconstruct every block immediately as the corresponding quantization indices are available, we propose an estimation-theoretic delayed decoding scheme which leverages quantization and motion information of one or more future frames to refine the reconstruction of the current block. The scheme, implemented in the transform domain, efficiently combines all available (including future) information in an appropriately derived conditional pdf, to obtain the optimal delayed reconstruction of each transform coefficient in the frame. Experiments demonstrate substantial gains over the standard H.264 decoder. The scheme learns the autoregressive model from information available to the decoder, and compatibility with the standard syntax and existing encoders is retained.
Combined source-channel vector quantization using deterministic annealing

The authors present a new approach to combined source-channel vector quantization. The method, derived within information theory and probability theory, utilizes deterministic annealing to avoid some local minima that trap conventional descent algorithms such as the generalized Lloyd algorithm. The resulting vector quantizers satisfy the necessary conditions for local optimality for the noisy channel case. They tested the method against several versions of the noisy channel generalized Lloyd algorithm on stationary, first order Gauss-Markov sources with a binary symmetric channel. The method outperformed other methods under all test conditions, with the gains over noisy channel GLA growing with the codebook size. The quantizers designed using deterministic annealing are also shown to behave robustly under channel mismatch conditions. As a comparison with a separate source-channel system, over a large range of test channel conditions, the method outperformed a bandwidth-equivalent system incorporating a Hamming code. Also, for severe channel conditions, the method produces solutions with explicit error control coding.
Hidden Markov model-based multi-modal image fusion with efficient training

Automated spatial alignment of images from different modalities is an important problem, particularly in bio-medical image analysis. We propose a novel probabilistic framework, based on a variant of the 2D hidden Markov model (2D HMM), to capture the deformation between multi-modal images. Smoothness is ensured via transition probabilities of the 2D HMM and cross-modality similarity via class-conditional, modality-specific emission probabilities. The method is derived for general multi-modal settings, and its performance is demonstrated for an application in cellular microscopy. We also present an efficient algorithm for parameter estimation. Experiments on synthetic and real biological data show improvement over state-of-the-art multi-modal image fusion techniques.
Predictive fusion coding of spatio-temporally correlated sources

This paper considers the problem of predictive fusion coding for storage of multiple spatio-temporally correlated sources so as to enable efficient selective retrieval of data from subsets of sources as designated by future queries. Only statistical information about future queries is available during encoding. While temporal correlations can be exploited by coding over large blocks, the growth in encoding complexity renders this approach impractical and hence the interest in a low complexity predictive coding approach. However, the design of optimal predictive fusion coding systems is considerably complicated by the presence of the prediction loop, and the potentially exponential growth of the query sets. We propose a complexity-constrained predictive fusion coder and derive an iterative algorithm for its design, which is based on the "Asymptotic Closed Loop" framework and hence, circumvents convergence and stability issues of traditional predictive quantizer design. The proposed predictive fusion coder optimizes the distortion - retrieval rate tradeoff, given a fixed storage capacity, and provides significant gains over storage schemes that perform only joint compression or memoryless fusion coding of all sources.
Towards jointly optimal spatial prediction and adaptive transform in video/image coding

This paper proposes a new approach to combined spatial (Intra) prediction and adaptive transform coding in block-based video and image compression. Context-adaptive spatial prediction from available, previously decoded boundaries of the block, is followed by optimal transform coding of the prediction residual. The derivation of both the prediction and the adaptive transform for the prediction error, assumes a separable first-order Gauss-Markov model for the image signal. The resulting optimal transform is shown to be a close relative of the sine transform with phase and frequencies such that basis vectors tend to vanish at known boundaries and maximize energy at unknown boundaries. The overall scheme switches between the above sine-like transform and discrete cosine transform (per direction, horizontal or vertical) depending on the prediction and boundary information. It is implemented within the H.264/AVC intra mode, is shown in experiments to significantly outperform the standard intra mode, and achieve significant reduction of the blocking effect.
Noisy channel relaxation for VQ design

We study the structure and design of a vector quantizer (VQ) for robust performance under noisy channel conditions. We develop some new insights about the geometrical structure of such a VQ, and introduce noisy channel relaxation-a novel design approach. In particular, the approach is used to attack two basic problems: (1) optimize the VQ for a given noisy channel; and (2) optimize index assignment while maintaining optimality for the noiseless channel. For problem (1) we show consistent improvements over descent methods at the cost of manageable increase in complexity (by a factor of up to three). For problem (2) we obtain index assignment with a quality significantly better than known methods, but at computational complexity that grows many times slower.
Interconnect strategies for deep submicron CMOS manufacture

As CMOS chips are scaled to deep submicron dimensions, interconnect strategy remains a key gateway for performance and manufacturability. ITRS'99 projections seriously underestimate the number of wiring levels required, even though inductance effects can significantly reduce wiring level requirements. By examining the requirements for a Multimedia Internet Processor, we project more reasonable wiring level requirements. The effects of alternative interconnect materials are considered, and the importance of appropriate interconnect strategies is emphasized.
Optimal mappings for joint source channel coding

What is the optimal source-channel communication system for a given finite block length? The problem of obtaining the vector transformations that optimally map between the m-dimensional source space and the k-dimensional channel space is considered under a given channel power constraint and mean square error distortion measure. Closed form necessary conditions for optimality of the encoder and decoder mappings are derived. The optimal mappings are obtained using an iterative algorithm that updates encoder and decoder mappings according to optimality conditions at each iteration. Such mappings are used in a practical analog joint source channel system that transmits a continuous alphabet discrete time source over a noisy channel. Numerical results are presented for several source-channel distributions and it is shown that the optimal mappings outperform the previous heuristic mappings for both bandwidth expansion and compression.
On the role of common codewords in quadratic Gaussian multiple descriptions coding

This paper focuses on the problem of L-channel quadratic Gaussian multiple description (MD) coding. We recently introduced a new encoding scheme in  for general L-channel MD problem, based on a technique called `Combinatorial Message Sharing' (CMS), where every subset of the descriptions shares a distinct common message. The new achievable region subsumes the most well known region for the general problem, due to Venkataramani, Kramer and Goyal (VKG) . Moreover, we showed in  that the new scheme provides a strict improvement of the achievable region for any source and distortion measures for which some 2-description subset is such that the Zhang and Berger (ZB) scheme achieves points outside the El-Gamal and Cover (EC) region. In this paper, we show a more surprising result: CMS outperforms VKG for a general class of sources and distortion measures, which includes scenarios where for all 2-description subsets, the ZB and EC regions coincide. In particular, we show that CMS strictly extends VKG region, for the L-channel quadratic Gaussian MD problem for all L ≥ 3, despite the fact that the EC region is complete for the corresponding 2-descriptions problem. Using the encoding principles derived, we show that the CMS scheme achieves the complete rate-distortion region for several asymmetric cross-sections of the L-channel quadratic Gaussian MD problem, which have not been considered earlier.
Transform-domain temporal prediction in video coding with spatially adaptive spectral correlations

Temporal prediction in standard video coding is performed in the spatial domain, where each pixel block is predicted from a motion-compensated pixel block in a previously reconstructed frame. Such prediction treats each pixel independently and ignores underlying spatial correlations. In contrast, this paper proposes a paradigm for motion-compensated prediction in the transform domain, that eliminates much of the spatial correlation before individual frequency components along a motion trajectory are independently predicted. The proposed scheme exploits the true temporal correlations, that emerge only after signal decomposition, and vary considerably from low to high frequency. The scheme spatially and temporally adapts to the evolving source statistics via a recursive procedure to obtain the cross-correlation between transform coefficients on the same motion trajectory. This recursion involves already reconstructed data and precludes the need for any additional side-information in the bit-stream. Experiments demonstrate substantial performance gains in comparison with the standard codec that employs conventional pixel domain motion-compensated prediction.
Deterministic annealing, constrained clustering, and optimization

In previous work the authors ( 1990) proposed the concept of deterministic annealing for the problem of clustering and vector quantization. This approach is summarized. The authors extend the clustering method to the constraint clustering method. Adding constraints to the deterministic annealing mechanism expands the variety of optimization problems which can be solved by this method. A brief presentation of the clustering approach is given. Two examples to which the constraint clustering approach can be applied are included.<<ETX>>
Design of a Switched Broad-Band Communications Network for Interactive Services

The congestion in broad-band communications networks resulting from the increased demand for interactive services is considered. It is shown that services such as a video library could not be provided to the majority of subscribers in a conventional CATV network. A design is developed for a space division multiplex broad-band network which can be expanded at minimum cost to meet an increasing demand for interactive services. The network contains two signal distribution networks: a cablecast system similar to the Rediffusion system, and a switched communication network providing point-to-point circuits for both one-way and two-way services. All broad-band signals are transmitted to the subscribers in the 1- to 10-MHz spectrum, permitting the use of twisted pair video cables and a minimum number of cable amplifiers. The broad-band cable network (BCN) is organized around 15 local switching exchanges and one central exchange. Multipoint switches in local exchanges under wired-logic circuit control connect individual subscriber communication lines to any channel. Crosspoint matrix switching groups in the local and central exchanges connect communication circuits in the broad-band communication network under programmed computer control. This network is accessed via links terminating on one channel of the multiposition switches. Per-subscriber costs are estimated to be 190 dollars for a cablecast system serving 3800 subscribers. Additional expenditures per subscriber of 40 dollars for fixed costs and 40 dollars for variable costs would provide interactive services. The range of interactive services provided would be extremely flexible, including both one-way video library service and point-to-point two-way communications.
Efficient SNR-scalability in predictive video coding

A new method is proposed for efficient SNR scalability in predictive video coding. It is of low complexity, and it is applicable to standard DCT-based video compression with motion compensation. Information that is only available to the enhancement layers is exploited to improve the quality of their frame prediction without compromising the usefulness of the compressed data provided by the base layer(s). More specifically, the next frame prediction for use by an enhancement-layer decoder is obtained by combining, or switching between transform coefficients from: i) the reconstructed base-layer frame; and ii) the predicted enhancement-layer frame. The combining rule depends on the compressed residual of the base layer, and on the parameters used for this compression. The method is applied to standard DCT-based predictive video coding, and preliminary simulation shows consistent, substantial improvement in the performance of enhancement layers. The proposed method may be easily combined with known temporal scalability methods to provide further improvement of the performance of enhancement layers over a wide range of bit rates.
Macroblock-based retransmission for error-resilient video streaming

This paper revisits the problem of source-channel coding for error-resilient video streaming. We propose a new method to enable adaptive redundancy in the bitstream: fine-grain retransmission. Redundancy decisions are made per macroblock (MB), which are locally adaptive and of low overhead, as opposed to coarse packet-level redundancy (e.g. forward error correction). In this scheme, the encoder jointly optimizes the coding mode and redundancy per MB. A corresponding algorithm is presented for exploiting this redundancy at the decoder. The proposed method is general in nature, and can be implemented on top of any (hybrid) video codec. An example implementation is provided, which uses the redundant slice mechanism of H.264 (JM 13.2 reference software). Simulation results show significant performance gains over conventional error-resilient coding techniques.
Comparative studies of noise limitations in superconducting thin-film radiation detectors

We report measurements on the noise limitations of superconducting thin films operating as thermal detectors (bolometers) and as current-dependent detectors. By making measurements in each mode on the same film it is possible to make a comparative study of the noise limitations for both detection mechanisms in the same device. Thin tin films with normal state sheet resistances on the order of 100 Ω per square have been studied. The devices were scribed to produce total normal state resistances on the order of 10 kΩ and were mounted in the vacuum chamber of a demountable tail Dewar so that they were not in direct contact with liquid helium. The resulting bolometers have response times and sensitivities similar to those of Martin and Bloor. The dominant noise mechanisms we have observed appear to be Johnson noise in the thermal mode and 1/f noise in the current mode. These results confirm previous conclusions regarding the sensitivity of these films as radiation detectors.