Balanced gait generations of a two-legged robot on sloping surface

In this paper, dynamically balanced gait generation problem of a 7-DOF two-legged robot moving up and down through the sloping surface is presented. The gait of the lower links during locomotion is obtained after assuming suitable trajectories for the swing leg and hip joint. The trunk motion is initially generated based on the concept of static balance, which is different from the well-known semi-inverse method and then checked for its dynamic balance calculated using the concept of Zero-Moment Point (ZMP). Lagrange–Euler formulation is attempted for the determination of joint torques. Average power consumption at each joint is then determined based on the computed torques. Moreover, the variations of dynamic balance margin and average power consumption are studied for both ascending and descending through the sloping surface. Both of them are found to be more for the ascending gait generation compared to those for the descending case. The effects of variations of the slope have also been studied on the average dynamic balance margin and power consumption for both the cases.     

Efficient parasitic substrate modeling for monolithic mixed-A/D circuit design and verification

Parasitic analog-digital noise coupling has been identified as a key issue facing designers of mixed-signal integrated circuits. In particular, signal crosstalk through the common chip substrate has become increasingly problematic. This paper demonstrates a methodology for developing simulation, synthesis, and verification models to analyze the global electrical behavior of the non-ideal semiconductor substrate. First, a triangular discretization method is employed to generate RC equivalent-circuit substrate models which are far less complex than those formulated by conventional techniques. The networks are then accurately approximated for subsequent analysis by an efficient reduction algorithm which uses a well-conditioned Lanczos moment-matching process. Through congruence transformations, the network admittance matrices are transformed to reduced equivalents which are easily post-processed to derive passive, SPICE-compatible netlist representations of the reduced models. The pure-RC properties of the extracted substrate networks are fully exploited to formulate an efficient overall algorithm. For validation, the strategy has been successfully applied to several mixed-signal circuit examples.     

Exploiting the Terahertz Band for Radionavigation

This paper demonstrates the feasibility of GPS-like ranging at terahertz (THz) frequencies. It is well established that GPS carrier signals are vulnerable to jamming via radio-frequency interference (RFI). As a result, there is a need for alternative radionavigation systems. THz signals offer a compelling option. Because of their high frequency (roughly ×100 higher than GPS), THz signals can be used to make highly precise range measurements. In addition, the large separation between the GPS and THz frequencies means that interference at GPS frequencies is very unlikely to impact the THz band. This paper lays the groundwork for a GPS-like ranging capability at THz frequencies. To this end, we identify key differences between THz hardware and GPS (radio frequency) hardware; we experimentally evaluate performance of a 0.30-THz system on a compact outdoor test range, and we introduce a measurement error model that highlights the distinctive role that multipath interference plays at THz frequencies.     

Minimal cost one-dimensional linear hybrid cellular automata of degree through 500

This letter is a supplement of the table of the minimal cost one-dimensional linear hybrid cellular automata with the maximum length cycle by Zhang, Miller, and Muzio [IEE Electronics Letters, 27(18):1625–1627, August 1991].This work was supported in part by Research Grants and Postgraduate Scholarships from the Natural Sciences and Engineering Research Council of Canada and by an equipment loan from the Canadian Microelectronics Corporation.     

数据转换器的衡量方法:演进历程

数据转换器有意义的衡量方法是什么?就数据转换器自身而言,它是相当容易定义的.数据转换器是通过模数转换器(ADC)将连续的电信号(即模拟信号)转换为数码字[以比特(bit)为单位]或反过来,通过数模转换器(DAC)将数码字转换为连续的模拟信号.这样的转换过程是我们周围的真实世界和我们用以监测、分析、控制的计算机世界之间的至关重要的连接.其中最困难和有发展意义的问题是如何为这些数据转换器定义重要的性能指标.     

Switched-capacitor filters using unity-gain amplifiers

Switched-capacitor networks realizing second-order filter characteristics are presented. Realization is achieved with unity-gain amplifiers as buffers. The circuits have small sensitivities, good dynamic range and a reasonable spread of capacitor values. The filters can be used for high-Q realization and a relatively high frequency range.     

Systematic design of wideband ΔΣ modulators for WiFi/WiMAX receivers

Modern multi-standard receivers in deep-submicron technologies pose significant design challenges on the analog baseband. Moving this analog filtering to the digital domain simplifies the design, yielding a process-scalable implementation. However, analog-to-digital converter (ADC) specifications now become more stringent and must be obtained by comprehending the standard and the system. Assuming a receiver NF of 5.96 dB and SNR degradation of 0.36 dB by the ADC, the proposed dual-mode WiFi/WiMAX receiver attains an input sensitivity of −74 dBm (20 MHz channel bandwidth). To accommodate the high dynamic range and the anti-alias rejection needed for the system, a Delta-Sigma (ΔΣ) ADC is proposed. Single-loop and Multi-Stage Noise-Shaping (MASH) architectures that achieve a SNR of 69 dB at a low oversampling ratio (OSR) of 8 for a conversion bandwidth of 40 MHz (108 Mbps, OFDM) are investigated at system level. Based on thermal noise, harmonic distortion, and power tradeoffs, a ΔΣ ADC design that meets the design specifications is presented.     

Automatic detection and segmentation of lymph nodes from CT data

Lymph nodes are assessed routinely in clinical practice and their size is followed throughout radiation or chemotherapy to monitor the effectiveness of cancer treatment. This paper presents a robust learning-based method for automatic detection and segmentation of solid lymph nodes from CT data, with the following contributions. First, it presents a learning based approach to solid lymph node detection that relies on marginal space learning to achieve great speedup with virtually no loss in accuracy. Second, it presents a computationally efficient segmentation method for solid lymph nodes (LN). Third, it introduces two new sets of features that are effective for LN detection, one that self-aligns to high gradients and another set obtained from the segmentation result. The method is evaluated for axillary LN detection on 131 volumes containing 371 LN, yielding a 83.0% detection rate with 1.0 false positive per volume. It is further evaluated for pelvic and abdominal LN detection on 54 volumes containing 569 LN, yielding a 80.0% detection rate with 3.2 false positives per volume. The running time is 5-20 s per volume for axillary areas and 15-40 s for pelvic. An added benefit of the method is the capability to detect and segment conglomerated lymph nodes.