Design of near allpass strictly stable minimal phase real valued rational IIR filters

In this brief, a near-allpass strictly stable minimal-phase real-valued rational infinite-impulse response filter is designed so that the maximum absolute phase error is minimized subject to a specification on the maximum absolute allpass error. This problem is actually a minimax nonsmooth optimization problem subject to both linear and quadratic functional inequality constraints. To solve this problem, the nonsmooth cost function is first approximated by a smooth function, and then our previous proposed method is employed for solving the problem. Computer numerical simulation result shows that the designed filter satisfies all functional inequality constraints and achieves a small maximum absolute phase error

Dynamic Phase Filtering with Integrated Optical Ring Resonators

Coherent optical signal processing systems typically require dynamic, low-loss phase changes of an optical signal. Waveform generation employing phase modulation is an important application area. In particular, laser radar systems have been shown to perform better with non-linear frequency chirps. This work shows how dynamically tunable integrated optical ring resonators are able to produce such phase changes to a signal in an effective manner and offer new possibilities for the detection of phase-modulated optical signals. When designing and fabricating dynamically tunable integrated optical ring resonators for any application, system level requirements must be taken into account. For frequency chirped laser radar systems, the primary system level requirements are good long range performance and fine range resolution. These mainly depend on the first sidelobe level and mainlobe width of the autocorrelation of the chirp. Through simulation, the sidelobe level and mainlobe width of the autocorrelation of the non-linear frequency modulated chirp generated by a series of integrated optical ring resonators is shown to be significantly lower than the well-known tangent-FM chirp. Proof-of-concept experimentation is also important to verify simulation assumptions. A proof-of-concept experiment employing thermally tunable Silicon-Nitride integrated optical ring resonators is shown to generate non-linear frequency modulated chirp waveforms with peak instantaneous frequencies of 28 kHz. Besides laser radar waveform generation, three other system level applications of dynamically tunable integrated optical ring resonators are explored in this work. A series of dynamically tunable integrated optical ring resonators is shown to produce constant dispersion which can then help extract complex spectral information. Broadband photonic RF phase shifting for beam steering of a phased array antenna is also shown using dynamically tunable integrated optical ring resonators. Finally all-optical pulse compression for laser radar using dynamically tunable integrated optical ring resonators is shown through simulation and proof-of-concept experimentation

Wavelet-based multi-carrier code division multiple access systems

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Synergy of Acoustic-Phonetics and Auditory Modeling Towards Robust Speech Recognition

The problem addressed in this work is that of enhancing speech signals corrupted by additive noise and improving the performance of automatic speech recognizers in noisy conditions. The enhanced speech signals can also improve the intelligibility of speech in noisy conditions for human listeners with hearing impairment as well as for normal listeners. The original Phase Opponency (PO) model, proposed to detect tones in noise, simulates the processing of the information in neural discharge times and exploits the frequency-dependent phase properties of the tuned filters in the auditory periphery along with the cross-auditory-nerve-fiber coincidence detection to extract temporal cues. The Modified Phase Opponency (MPO) proposed here alters the components of the PO model in such a way that the basic functionality of the PO model is maintained but the various properties of the model can be analyzed and modified independently of each other. This work presents a detailed mathematical formulation of the MPO model and the relation between the properties of the narrowband signal that needs to be detected and the properties of the MPO model. The MPO speech enhancement scheme is based on the premise that speech signals are composed of a combination of narrow band signals (i.e. harmonics) with varying amplitudes. The MPO enhancement scheme outperforms many of the other speech enhancement techniques when evaluated using different objective quality measures. Automatic speech recognition experiments show that replacing noisy speech signals by the corresponding MPO-enhanced speech signals leads to an improvement in the recognition accuracies at low SNRs. The amount of improvement varies with the type of the corrupting noise. Perceptual experiments indicate that: (a) there is little perceptual difference in the MPO-processed clean speech signals and the corresponding original clean signals and (b) the MPO-enhanced speech signals are preferred over the output of the other enhancement methods when the speech signals are corrupted by subway noise but the outputs of the other enhancement schemes are preferred when the speech signals are corrupted by car noise

Intelligent Tools for Multitrack Frequency and Dynamics Processing

PhDThis research explores the possibility of reproducing mixing decisions of a skilled audio engineer with minimal human interaction that can improve the overall listening experience of musical mixtures, i.e., intelligent mixing. By producing a balanced mix automatically musician and mixing engineering can focus on their creativity while the productivity of music production is increased. We focus on the two essential aspects of such a system, frequency and dynamics. This thesis presents an intelligent strategy for multitrack frequency and dynamics processing that exploit the interdependence of input audio features, incorporates best practices in audio engineering, and driven by perceptual models and subjective criteria. The intelligent frequency processing research begins with a spectral characteristic analysis of commercial recordings, where we discover a consistent leaning towards a target equalization spectrum. A novel approach for automatically equalizing audio signals towards the observed target spectrum is then described and evaluated. We proceed to dynamics processing, and introduce an intelligent multitrack dynamic range compression algorithm, in which various audio features are proposed and validated to better describe the transient nature and spectral content of the signals. An experiment to investigate the human preference on dynamic processing is described to inform our choices of parameter automations. To provide a perceptual basis for the intelligent system, we evaluate existing perceptual models, and propose several masking metrics to quantify the masking behaviour within the multitrack mixture. Ultimately, we integrate previous research on auditory masking, frequency and dynamics processing, into one intelligent system of mix optimization that replicates the iterative process of human mixing. Within the system, we explore the relationship between equalization and dynamics processing, and propose a general frequency and dynamics processing framework. Various implementations of the intelligent system are explored and evaluated objectively and subjectively through listening experiments.China Scholarship Council

Iterative Separation of Note Events from Single-Channel Polyphonic Recordings

This thesis is concerned with the separation of audio sources from single-channel polyphonic musical recordings using the iterative estimation and separation of note events. Each event is defined as a section of audio containing largely harmonic energy identified as coming from a single sound source. Multiple events can be clustered to form separated sources. This solution is a model-based algorithm that can be applied to a large variety of audio recordings without requiring previous training stages. The proposed system embraces two principal stages. The first one considers the iterative detection and separation of note events from within the input mixture. In every iteration, the pitch trajectory of the predominant note event is automatically selected from an array of fundamental frequency estimates and used to guide the separation of the event's spectral content using two different methods: time-frequency masking and time-domain subtraction. A residual signal is then generated and used as the input mixture for the next iteration. After convergence, the second stage considers the clustering of all detected note events into individual audio sources. Performance evaluation is carried out at three different levels. Firstly, the accuracy of the note-event-based multipitch estimator is compared with that of the baseline algorithm used in every iteration to generate the initial set of pitch estimates. Secondly, the performance of the semi-supervised source separation process is compared with that of another semi-automatic algorithm. Finally, a listening test is conducted to assess the audio quality and naturalness of the separated sources when they are used to create stereo mixes from monaural recordings. Future directions for this research focus on the application of the proposed system to other music-related tasks. Also, a preliminary optimisation-based approach is presented as an alternative method for the separation of overlapping partials, and as a high resolution time-frequency representation for digital signals

Beyond key velocity: Continuous sensing for expressive control on the Hammond Organ and Digital keyboards

In this thesis we seek to explore the potential for continuous key position to be used as an expressive control in keyboard musical instruments, and how preexisting skills can be adapted to leverage this additional control. Interaction between performer and sound generation on a keyboard instrument is often restricted to a number of discrete events on the keys themselves (notes onsets and offsets), while complementary continuous control is provided via additional interfaces, such as pedals, modulation wheels and knobs. The rich vocabulary of gestures that skilled performers can achieve on the keyboard is therefore often simplified to a single, discrete velocity measurement. A limited number of acoustical and electromechanical keyboard instruments do, however, present affordances of continuous key control, so that the role of the key is not limited to delivering discrete events, but its instantaneous position is, to a certain extent, an element of expressive control. Recent evolutions in sensing technologies allow to leverage continuous key position as an expressive element in the sound generation of digital keyboard musical instruments. We start by exploring the expression available on the keys of the Hammond organ, where nine contacts are closed at different points of the key throw for each key onset and we find that the velocity and the percussiveness of the touch affect the way the contacts close and bounce, producing audible differences in the onset transient of each note. We develop an embedded hardware and software environment for low-latency sound generation controlled by continuous key position, which we use to create two digital keyboard instruments. The first of these emulates the sound of a Hammond and can be controlled with continuous key position, so that it allows for arbitrary mapping between the key position and the nine virtual contacts of the digital sound generator. A study with 10 musicians shows that, when exploring the instrument on their own, the players can appreciate the differences between different settings and tend to develop a personal preference for one of them. In the second instrument, continuous key position is the fundamental means of expression: percussiveness, key position and multi-key gestures control the parameters of a physical model of a flute. In a study with 6 professional musicians playing this instrument we gather insights on the adaptation process, the limitations of the interface and the transferability of traditional keyboard playing techniques