Chenchi Luo

Compressive Sensing for Sparse Touch Detection on Capacitive Touch Screens

Capacitive touch screens are ubiquitous in todays electronic devices. Improved touch screen responsiveness and resolution can be achieved at the expense of the touch screen controller analog hardware complexity and power consumption. This paper proposes an alternative compressive sensing based approach to exploit the sparsity of simultaneous touches with respect to the number of sensor nodes to achieve similar levels of responsiveness. It is possible to reduce the analog data acquisition complexity at the cost of extra digital computations with less total power consumption. Using compressive sensing, in order to resolve the positions of the sparse touches, the number of measurements required is related to the number of touches rather than the number of nodes. Detailed measurement circuits and methodologies are presented along with the corresponding reconstruction algorithm.

Compressive sampling with a successive approximation ADC architecture

This paper proposes a compressive sampling scheme based on random temporal sampling using a successive approximation register (SAR) ADC architecture. Variable wordlength data samples at random sampling times would be produced by the SAR converter, so a modified reconstruction algorithm is proposed to recover signals that are sparse or compressible in a known basis. The modified reconstruction algorithm addresses the variable wordlength resolution issue of SAR ADC samples introduced by the random sampling scheme. We demonstrate that the proposed sampling and reconstruction scheme performs significantly better compared with uniform sampling on the same SAR ADC architecture.

Discrete random sampling theory

This paper proposes a new perspective on the relationship between the sampling and aliasing. Unlike the uniform sampling case, where the aliases are simply periodic replicas of the original spectrum, random sampling theory shows that the randomization of sampling intervals shapes the aliases into a noise floor in the sampled spectrum. New insights into both the Fourier random sampling problem and Compressive Sensing theory can be obtained using the theoretical framework of random sampling. This paper extends the theory of continuous time random sampling to deal with random discrete intervals generated from a clock. A key result is established to relate the discrete probability distribution of the sampling intervals to the power spectrum of the aliasing noise. Based on the proposed theory, a generic discrete random sampling hardware architecture is also proposed for sampling and reconstructing a class of spectrally sparse signals at an average rate significantly below the Nyquist rate of the signal.

Sparse touch sensing for capacitive touch screens

Improved capacitive touch screen responsiveness can be achieved at the expense of the touch screen controller analog hardware complexity and power consumption. This paper proposes a compressive sensing based approach to exploit the sparsity of simultaneous touches (e.g., 10 or less per person) with respect to the number of sensor nodes (e.g., 100s) to achieve similar levels of responsiveness with lower levels of analog complexity and power consumption. This is done by showing that the number of measurements required for touch detection is related to the number of touches rather than the number of nodes.

Coordinated blind calibration for time interleaved ADCS

This paper presents a novel digital blind calibration method for time interleaved analog to digital converters (TIADCs). A simple cost function based on the cross-correlation of channel statistics is used to derive a steepest descent algorithm for the compensation of timing mismatch errors. Instead of calibrating the timing mismatches independently for each channel, only one adaptation channel needs to be calibrated within a closed loop. The calibration of the rest of the channels can be coordinated according to a scaling relationship established during an initialization stage. As a result, both the computational complexity and convergence speed of the proposed algorithm can be improved significantly with little loss in calibration performance.

Cyclostationarity-based wideband spectrum sensing using random sampling

Cognitive radio (CR) systems offer higher spectrum utilization by opportunistically allocating the unused spectrum from primary users to secondary users. For CR it is vital to perform fast and accurate spectrum sensing in a wideband and noisy channel. Cyclic feature detection performs well in signal detection and is also highly robust to noise uncertainty. However, it requires a high sampling rate when operating over a wideband channel. Based on the sparsity of the cyclic spectrum, compressive sampling technique can extend sparse reconstruction to its case. This paper develops a simpler cyclic spectrum recovery method based on random sampling and demonstrates faster and better performance. Recent research on discrete random sampling provides a new connection between sub-Nyquist sampling and aliasing as a noise floor that can be dynamically shaped by different distributions of sampling times. Practical analog-to-digital converters can implement these random sampling schemes. Thus, a reduced hardware complexity cyclic feature detector based on the reconstructed cyclic spectrum is proposed to identify the spectrum occupancy within the entire wideband.

Adjustable bandwidth filter design with generalized farrow structure

Digital filters with adjustable bandwidth(s) are generally desirable in many applications like audio processing and telecommunication. This paper proposes a generalized Farrow structure for adjustable bandwidth linear-phase FIR filters designed under a minimax design criterion. The bandwidth of the proposed filter structure can be continuously adjusted with an updating routine that only involves a few multiplications and additions. Moreover, the generalized structure can be designed to effectively reduce the dynamic range of basis filter coefficients, which is desirable when making a fixed-point implementation on FPGAs.

A general structure for the design of adjustable FIR filters

This paper proposes a general structure for FIR filters with adjustable magnitude and phase responses controlled by a few parameters. The Farrow structure which uses one parameter to control the fractional delay of an FIR filter can be viewed as special case. A filter bank structure consisting of different types of linear phase differentiators forms the basis of the structure. The filter bank outputs are combined with coefficients derived from a polynomial expansion of the desired frequency response. The magnitude and phase responses are controlled by synthesizing the polynomial coefficients from the small set of control parameters. A new optimal polynomial approximation strategy is also proposed to better approximate the family of target frequency responses.

Introductory signal processing labs based on filterbank applications

Filterbank implementations and simulations can be used successfully in introductory signal processing lab courses by avoiding some of the analytical complexities and focusing on real-world applications. One excellent area is human hearing where the cochlea is well modelled by a filterbank. A lab project that simulates a cochlear implant (CI) combines elements of signal processing with biomedical engineering. Another intriguing application is the decoding of dual-tone multiple-frequency (DTMF) signals used in telephones. Designing a filterbank with multiple bandpass channels to extract signal of interest motivates students to learn filter design, and also provides them with a sense of accomplishment once the whole system is is working. In addition, these filterbank labs can be supported with graphical user interfaces (GUIs) that illustrate how the important components of the system must work together. A comprehensive GUI for the CI simulation is presented along with a GUI tool for filter design. The CI GUI shows the expected signal behavior in the channels after filtering and after detection, as well as having sound input-output, so that students can listen to the key signals.

A model based excursion protection algorithm for loudspeakers

Loudspeakers in portable consumer electronic devices are frequently small in size. Due to the low sensitivity of their drive units, they are pushed to their power handling and mechanical limits by powerful amplifiers in an attempt to reach high volumes. To protect against excessive diaphragm excursions, a model based algorithm is proposed which regulates the voltage input signal to the loudspeaker while minimizing unnecessary system interventions.