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Cacao pod's ideal harvesting time is when it is about to be ripe. Immature harvest would result in hard cacao beans not suitable for fermentation, while overripe cacao pods lead to fungal-infected, defective, and poor-quality yields. The demand for high-quality cacao products is expected to rise due to advancing technology in the present. Pre-harvesting needs to provide optimal identification of which amongst the pods are ripened enough and ready for the next stage of the cacao process. This paper recommends a technique to determine the ripeness of cacao. Nine hundred thirty-three cacao samples were used to collect thumping audio data at five different pod's exocarp locations. Each sound file is 1 second long, creating 4665 cacao sound file datasets at 16kHz sample rate and 16-bit audio bit depth. The process of the Mel-Frequency Cepstral Coefficient Spectogram was then applied to extract recognizable features for the training process. The deep learning method integrated was a convolutional neural network (CNN) to classify the cacao sound successfully. The experimental design model's output exhibits an accuracy of 97.50 % for the training data and 97.13 % for the validation data. While the overall accuracy mean of the classification system is 97.46 %, whether the cacao is unripe or ripe.

The study aimed to filter and remove noise from audio, and in this study researcher followed the descriptive analytical method. The study sample consisted of an audio file and has been save Audio of on a formula (WAV), and the study used matlab 7.10.0 to read sound and design low pass filter, then insert the audio signal with the noise signal into the filter and output a signal audio without noise. The researcher has reached findings that differed according to the rank of the filter. The low pass filter has a great effect on removing noise during the registration process together with the times of implementation.

Human auditory system is highly sensitive that can detect or discriminate subtle changes in an audio. The direct least significant bit (LSB) substitution scheme, often used in image steganography, cannot be effective for audio steganography to provide secrecy needed for many audio applications, because the embedded secret bits in the LSBs of the audio samples in a silent or near silent segment of an audio can produce strong hissing noise when played. In this work, governed by an error criterion, we present a multi-threshold-based scheme for audio steganography. In order to evade detection by means of any statistical or perceptual analysis of the resultant audio, the threshold values are derived from an error criterion that can be used to limit the number of bits to be embedded in an audio sample. To defend against retrieval of bits by an adversary as well as to dissipate any pattern in the resultant audio, a scheme for chaotic distribution of the secret message bits in the cover audio is also proposed. In comparison with most recently proposed schemes in literature, our proposed scheme exhibits better performance against statistical and perceptual analysis for the same embedding capacity. Our proposed scheme can be used to increase the capacity of the cover audio in a controlled manner by adjusting the error criterion.

This article presents a 3rd Order 1-bit ΔΣ modulator optimized for applications requiring high effective resolution and linearity within the 20-kHz band. Furthermore, this work also describes architectural approaches for designing modulators with different order, oversampling rate, and number of quantization bits. Such approaches can be leveraged in a variety of applications in digital signal processing for data communications, filters, motor controllers, data acquisition, high-fidelity audio, DACs, and others operating in baseband. The 3rd Order modulator was implemented in standard 180nm CMOS; experimental measurements show a SNDR=126dB equivalent to 20-bits of effective resolution with a total harmonic distortion THD=0.03%. The circuit is able to operate in low-voltage conditions from 0.55 to 1.8 Volts.

The weakness of Human Auditory System (HAS) led the audio steganography process to be used in hiding data in the digital sound. Audio steganography is implemented here by using Least Significant Bit (LSB) algorithm to hide message into multiple audio files. This is achieved by 1st, 2nd, 3rd, and 4th bits hiding ratios. In comparison to other used bits, hiding results show that the use of 1st bit in LSB method for embedding data is much better than those used bits as expected. In addition to that and according to the results, file’s size affects strongly upon the effectiveness of the embedding process while hiding starting position doesn’t affect upon the variation of the adopted statistical estimators regardless to which bit is used. Among the statistical estimators that have been adopted here, the Mean Absolute Error (MAE) seems to be the best one in testing hiding process.

In this paper, we propose a method for detecting marks of lossy compression encoding, such as MP3 or AAC, from PCM audio. The method is based on a convolutional neural network (CNN) applied to audio spectrograms and trained with the output of various lossy audio codecs and bitrates. Our method shows good performances on a large database and robustness to codec type and resampling.

Future infrared remote sensing systems, such as monitoring of the Earth’s environment by satellites, infrastructure inspection by unmanned airborne vehicles etc., will require 16 bit depth infrared images to be compressed and stored or transmitted for further analysis. Such systems are equipped with low power embedded platforms where image or video data is compressed by a hardware block called the video processing unit (VPU). However, in many cases using two 8-bit VPUs can provide advantages compared with using higher bit depth image compression directly. We propose to compress 16 bit depth images via 8 bit depth codecs in the following way. First, an input 16 bit depth image is mapped into 8 bit depth images, e.g., the first image contains only the most significant bytes (MSB image) and the second one contains only the least significant bytes (LSB image). Then each image is compressed by an image or video codec with 8 bits per pixel input format. We analyze how the compression parameters for both MSB and LSB images should be chosen to provide the maximum objective quality for a given compression ratio. Finally, we apply the proposed infrared image compression method utilizing JPEG and H.264/AVC codecs, which are usually available in efficient implementations, and compare their rate-distortion performance with JPEG2000, JPEG-XT and H.265/HEVC codecs supporting direct compression of infrared images in 16 bit depth format. A preliminary result shows that two 8 bit H.264/AVC codecs can achieve similar result as 16 bit HEVC codec.

By the end of this book, we know many things about the professional and personal life of Cassini and his family. He dealt with an impressive list of astronomical and also non-astronomical problems, collecting many successes and rewards, and leaving an important heritage to future generations. But this is not the whole story yet, and among his activities there are “shadows” among the lights, as well as some curious aspects that are worth mentioning. In this last chapter, therefore, we want to list some of these less known facts: “defaillances”, failures, the design of particular objects, and his last project connected to the city of Bologna.

This paper presents a system of audio signal processing based on FPGA,the system uses audio codec chip LM4550 to A/D transform and D/A transform the input analog audio signal and output digital audio signal.Using FPGA as the high speed signal processor to realize volume adjustment and audio effect control,so it can output different style music.Meantime, the system designs a FFT computing module and control system of VGA display interface,to compute the digital audio signal which is A/D transformed,and real-time display the frequency spectrum of audio signal on VGA.

Compared to most digital data types, with the exception of digital audio, the data rates associated with uncompressed digital audio are substantial. Digital audio compression enables more efficient storage and transmission of audio data. The many forms of audio compression techniques offer a range of encoder and decoder complexity, compressed audio quality, and differing amounts of data compression. In this paper a new algorithm for speech signals compression using wavelet transform technique with Discrete Cosine Transform (DCT) technique. The performance of the implemented algorithm is evaluated based on Signal to Noise Ratio (SNR), Root Mean Square Error (MSE) and compression ratio tested on speech signals. In this paper a Wavelet & cosine hybrid model, based speech coder is implemented in software using Matlab.

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Zero-watermark technique, embedding watermark without modifying carriers, has been broadly applied for copyright protection of images. However, there is little research on audio zero-watermark. This paper proposes an audio zero-watermark scheme based on energy relationship between adjacent audio sections. Taking use of discrete wavelet transformation (DWT), it gets power approximations, or energies, of audio segments. Then, it extracts the audio profile, i.e. the zero-watermark, according to the relative size of energies of consecutive fragments. The experimental results demonstrate that the proposed scheme is robust against general malicious attacks including noise addition, resampling, low-pass filtering, etc., and this approach effectively solves the contradiction between inaudibility and robustness.

A new approach to design a DAB audio decoder is introduced to improve the quality of audio at the receiver end. Integrating an MPEG-1 Layer II (MP2) decoder and Advanced Audio Coding Low Complexity (AAC LC) decoder provides basic audio decoding for DAB in FPGA. The audio frames data are generated from DAB channel decoder are stored in RAM. The bit stream Demultiplexer parses the quantized spectrum data in the audio frame and stores them in to the audio RAM. The inverse quantization block reads the quantized spectra from the audio RAM, performs the inverse quantization computations, and writes back the result to the audio RAM. The synthesis filter reads the inverse quantized spectra from the audio RAM, generates the time domain Pulse Code Modulation (PCM) samples, and writes them back to the audio RAM. The whole projects run by using XILINX 12.1 ISE. Finally analyze the power consumption and area occupied by the designed architecture.

This paper addresses the following problem in networked control: “If a control law is implemented over a channel that supports a certain fixed bit rate what is the best choice for the control update rate and, consequently, the number of bits carried in each sample?” A restricted architecture in which linear filters are used for the encoder/decoder is considered and a quantizer with linear feedback is deployed. Subject to these restrictions, a procedure for designing the controller and associated filters is presented. These filters are then deployed to choose the best number of bits per control update. It is shown, subject to the above restrictions, that it is generally best to use one bit per sample, in which case, the control update rate is equal to the bit rate. Our analysis has two points of departure from contemporary literature in this area. Firstly, we focus on bits per unit time, as opposed to bits per sample. Secondly we use a fixed number of bits in every time period as opposed to an average bit rate.

In this paper, we present the study of audio signal denoising, recognizing its audio type and retrieving similar signals from the database. Primarily the signal is denoised to remove any noise present in the unknown signal. Time Frequency Block Thresholding is used to achieve this. Removing the noise from audio signals requires processing of time-frequency coefficients in order to keep away from producing the musical noise. A block thresholding estimation procedure is introduced, which relates the parameters adaptively to signal property. Content Based Audio Retrieval system is very useful to identify the unknown audio signals. Audio signals are classified into music, speech and background sounds. This is done by the use of various feature vectors such as zero crossing rate, spectral centroid, spectral flux, spectral roll off. Use of multiple feature vectors improves the accuracy of the results being retrieved from the audio database. Various experiments demonstrate the performance and accurateness, providing good results for non standard signals.

Digital format of data has become very popular now a days with the advancement of technology. But the problem arises when unauthorized copying and distribution of these digital contents took place. As a result the question of copyright protection came. In order to cope with this situation, the era of Digital Watermarking came where the authorized owner hides some kind of information in an imperceptible way into the digital data. Digital Audio Watermarking is a technique to hide information in a host audio file in such a way that it is imperceptible to the listener. It is used for the copyright protection, tamper proofing of any multimedia file. In this paper a robust and efficient audio zero-watermarking algorithm is introduced. Audio zero-watermarking is an embedding technique in which the watermark does not modify the original audio file as it is hidden into a secret key. In this technique, 1-level DWT and DCT are done on the host audio and then a logical key is generated. Experimental results show that the proposed scheme is efficient and the watermarked signal is indistinguishable from the host audio signal as no modification is done in the original audio. This scheme provides high robustness against the desynchronization attacks and common attacks like cropping, noise addition, re-sampling, re-quantization, lowpass filtering, MP3 compression etc. In order to evaluate the performance of the proposed watermarking method, we have shown the respective BER and Normalized correlation (NC) values.

Unauthorized copying and distribution of digital audio has been greatly facilitated by the wide availability of low-cost personal computers, portable devices, network access, and audio recording and editing software. One possible solution for copyright protection is audio watermarking. In this paper, we propose an effective and robust audio watermarking algorithm that employs both the discrete wavelet transform and the discrete cosine transform. The algorithm involves, first, pre-processing of the binary watermark image and then embedding it into the original audio by quantization of coefficients. Experiments on audio recordings of many different music styles confirm the robustness of the algorithm against a wide range of Stirmark attacks such as noise addition, compression, and filtering, as well as other common attacks.

This paper presents a technique for low bit rate compression of three-dimensional (3D) audio produced by multiple loudspeaker channels. The approach is based on the time-frequency analysis of the localization of spatial sound sources within the 3D space as rendered by a multi-channel audio signal (in this case 16 channels). This analysis results in the derivation of a stereo downmix signal representing the original 16 channels. Alternatively, a mono-downmix signal with side information representing the location of sound sources within the 3D spatial scene can also be derived. The resulting downmix signals are then compressed with a traditional audio coder, resulting in a representation of the 3D soundfield at bit rates comparable with existing stereo audio coders while maintaining the perceptual quality produced from separate encoding of each channel. © 2006-2012 IEEE.

We propose a simple prior for restoration problems involving oscillatory signals. The prior makes use of an underlying analytic frame decomposition with narrow subbands. Other than this, the prior does not have any other parameters, which makes it simple to use and apply. We demonstrate the utility of the proposed prior through some real audio restoration experiments.

This paper discusses the issue of tradeoff between image size and performance in PSNR on bit plane image. A bit plane of a digital discrete signal is a set of bits indicate a presented bit plane in each of the binary numbers depicting the image. Image can be converted into a series of binary signal by shattering them up into their bit planes. The 0thbit plane is the least significant bit and the last bit plane is the most significant bit. Experimental results show that the best tradeoff is using the third to the seventh bit planes.

A kind of multifunctional audio digital watermark algorithm was put forward according to the copyright protection of audio problems. The audio signal is layered three by wavelet packet decomposition and robust watermark is embedded in the low frequency part, fragile watermark is embedded in the intermediate frequency part. The experimental results show that, the algorithm has no sound very good, excellent robustness and fragility. In the actual use of the process, which not only guarantees the safety of audio information effectively , but also guarantees good audio information fidelity.

A digital input class-D audio amplifier is presented for digital hearing aid. The class-D audio amplifier is composed of digital and analog circuits. The analog circuit converts a digital input to a analog audio signal (DAC) with noise suppression in the audio band. An interpolated digital delta-sigma modulator is used to convert data types between digital signal processor (DSP) and digital-to-analog converter (DAC). An 16-bit, 25-kbps pulse code modulated (PCM) input is interpolated to 16-bit, 50-kbps by a digital filter. The output signal of interpolation filter is noise-shaped by a third-order digital sigma-delta modulator (SDM). As a result, 1.5-bit, 3.2-Mbps signal is applied to simple digital to analog converter.

A audio compressor is an important part of a audio processing system. The compression algorithm designed in this paper will be applied to audio compressor in the digital audio broadcasting transmitter. In this paper, an effective algorithm for dynamic control of the gain by taking mean square value is proposed, and two different audio signal from two channel processing schemes will be compared to get better one on the impact of compression. Then the algorithm is evaluated by the effect of compression of signal amplitude in the MATLAB simulation, and a scheme selected that signal is firstly dealt with to enhance the effect of the dual channel stereo and then is compressed is more suitable for the two channel audio compression from two schemes.

DRA (Dynamic Resolution Algorithm) is referred to specification for multi-channel digital audio coding technology which was issued as a Chinese national standard in 2008. A low bit rate audio coding algorithm based on DRA is presented in the paper with a significant improvement in the coding efficiency of DRA at 32kbps/stereo by BWE (BandWidth Extension) and PS (Parametric Stereo) tools, and it was adopted as the source coding of CDR (Chinese Digital Radio).

The increasing emergence of hybrid drill bit technologies in recent years is pushing drilling performance to new levels that were previously unattainable by conventional designs. One example of a hybrid bit technology uses a combination of gouging inserts and shearing PDC cutters to increase the overall effectiveness of rock removal. In two and a half years of development, this hybrid gouging / shearing cutting structure has consistently demonstrated a superior average ROP over rollercone bits, as well as improved PDC cutter durability and lower reactive torque compared to traditional PDC bits. Until recently, the majority of gouging / shearing hybrid bit applications were in surface intervals drilled by six-bladed, 16mm cutter designs. This configuration is adept in enhancing ROP and durability in challenging formations such as gravel and boulders, which normally cause severe impact damage to PDC cutters. However, to push the benefits of the hybrid technology into new territory, significant design changes were made to optimize its performance in the newly targeted applications. In high ROP intervals, lowering the blade count of the bit has been shown to provide two key benefits: firstly, reduced cutter density increases the depth of cut and work rate for each PDC cutter, thereby increasing the aggressiveness and ROP potential of the design. Secondly, it enables more geometrical freedom for a hydraulic configuration that better suits high ROP and thermal demands. Unlike the six- bladed designs, the hydraulic layout of the reduced blade count designs incorporates separate nozzles dedicated to both the gouging inserts and PDC cutters on each blade. The ability to direct high velocity drilling fluid to both cutting structures promotes more effective cooling and removal of cuttings. The first instance of the updated hybrid technology was realized with a four-bladed, 12.25 in. diameter design used in a series of runs in Western Canada, drilling competent formations consisting primarily of shale with interbedded sandstones. The hybrid runs in these areas have exceeded the ROP typically achieved by six-bladed PDC bits in offset wells, and in certain cases, recorded average ROPs of over 310 ft/hr while still maintaining superior torque management throughout the entire run. Additionally, the dull conditions of the bits have repeatedly demonstrated reduced PDC cutter impact damage and thermal wear compared to conventional PDC designs. More development is currently underway to further expand lighter-set hybrid designs into more diverse applications.

This paper presents an implementation of a high power 32-bit Ternary Digital to Analog Converter (“TriDAC”) with a new topology, originally designed as a stimulus generator for audiometry, capable of a very high dynamic range of more than 170 dB.

Audio sample bit modification for steganography and watermarking is a viable technique with a simple time domain procedure. While high bit index is needed for robustly carrying hidden data in the presence of noise and low level attacks, an indication of tampering or verification of authenticity of received audio can be ensured using a fragile watermark spread throughout the audio. In this paper, an audio watermarking procedure for hiding an imperceptible and fragile watermark using bit modification is presented. Altering or attacking the watermarked audio, simulated by adding Gaussian noise, showed that the watermark was lost at an SNR of no less than 100 dB for a noise-free speech from the TIMIT database or for a noisy audio from communication from an aircraft cockpit, even when the perceptual quality of the audio in both cases remained the same as the original audio.

Steganography is the art of science dealing with hiding secret data inside image, audio, video or text files. In audio steganography; secret message is embedded in the digital sound by slightly altering the binary sequence of the sound file. Existing audio steganography software deal with WAV, AU, and even MP3 sound files. Embedding secret messages in the digital sound is usually a more difficult process than embedding messages in other forms, such as digital images. Audio steganography uses different algorithms, but (LSB) least significant bit is applied in this paper. The quality of sound is depended on the size of the audio which the user selects and length of the message.

In this paper, a robust wavelet based watermarking scheme has been proposed for digital audio. A single bit is embedded in the approximation part of each frame. The watermark bits are embedded in two subsets of indexes randomly generated by using two keys for security purpose. The embedding process is done in adaptively fashion according to the mean of each approximation part. The detection of watermark does not depend on the original audio. To measure the robustness of the algorithm, different signal processing operations have been applied on the watermarked audio. Several experimental results have been conducted to illustrate the robustness and efficiency of the proposed watermarked audio scheme.

Digital audio watermarking embeds inaudible information into digital audio data for the purposes of copyright protection, ownership verification, covert communication, and/or auxiliary data carrying. In this paper, we present a novel watermarking scheme to embed a meaningful gray image into digital audio by quantizing the wavelet coefficients (using integer lifting wavelet transform) of audio samples. Our audio-dependent watermarking procedure directly exploits temporal and frequency perceptual masking of the human auditory system (HAS) to guarantee that the embedded watermark image is inaudible and robust. The watermark is constructed by utilizing still image compression technique, breaking each audio clip into smaller segments, selecting the perceptually significant audio segments to wavelet transform, and quantizing the perceptually significant wavelet coefficients. The proposed watermarking algorithm can extract the watermark image without the help from the original digital audio signals. We also demonstrate the robustness of that watermarking procedure to audio degradations and distortions, e.g., those that result from noise adding, MPEG compression, low pass filtering, resampling, and requantization.

In the present scenario of extensive mediums for communication technologies, it has always been a challenging task to ensure the confidentiality of the sensitive information that is transmitted over a secured channel. Amongst various reliable and efficient techniques to secretly exchange information, Audio Steganography is considered very promising. LSB technique for Audio Steganography is very efficient that embeds the secret message with an audio file by replacing LSBs of that audio. In this paper Random Key Indexing method is proposed to replace the LSBs of the carrier audio with secret message. The bit replacement is guided by primary key that is provided by TTP (Trusted Third Party) and secondary key that will be generated at encoder end during embedding process and is supplied to the decoder end. The proposed method also uses message retrieval code that adds another layer of protection to the process. The method is successfully tested on various 32 bit & 16 bit stereo wave files with different payloads. The SNRdb values comes out be in the range 139 dB to 142 dB for 32 bit and 67 dB to 85 dB for 16 bit stereo files. The Bit Error Rate (BER) comes out be in the range 0.23 to 0.32 percent for 32 bit and 0.018 to 0.028 percent for 16 bit files.

In this paper a robust audio steganography method is introduced which involves multiple layers for embedding secret data. In LSB technique generally a single or multiple bits are embedded always in one or some particular bit positions. So it is easy to get that data by knowing those positions. The robustness increases in LSB approach by considering higher LSB layer but it reduces the perceptibility of audio. Here in this proposed work LSB embedding is used in multiple layers and also capacity is increased by embedding two bits at a time. Here always two different pairs 01 and 11 are embedded instead of four, made using two bits at a time at the same time increases robustness more. Without knowing the bitwise operation applied here for extraction it is not also very much easy to get the actual data. After embedding flag setting and bit adjustment is done for maintaining the perceptual transparency of stego audio. Here in this proposed work capacity is also increased by considering 6 bit binary instead of 7 or 8.

This paper presents a digital audio watermarking scheme that can embed imperceptible and robust watermark image into the audio signal. The watermarking process is performed in discrete wavelet domain by applying the QR factorization on 2-D blocks of low frequency part. The watermark bits are inserted in each block by quantizing the coefficients of resulting R matrices. A particle swarm optimization technique is designed to find an optimal quantization step which allows to obtain the highest possible robustness without losing the transparency of the watermark. A series of experiments has been carried out by using different host audio signals under different attacks. Results show that the audio quality is maintained and the watermark remains robust despite various signal processing attacks. In comparison with some recent audio watermarking algorithms, our method presents competitive results in terms of imperceptibility and robustness.

In this article, we present and analyze a new family of fixed-point data formats for signal processing applications. These formats represent compressed two's complement data formats where compression on the sign bit is undertaken on a sample by sample basis. The extra room provided by sign-bit compression is utilized to retain more bits of precision for each individual sample. Compressed two's complement data formats are shown to provide greater dynamic range and improved noise performance over traditional fixed-point data formats such as sign-magnitude, offset binary, and traditional two's complement. Traditional two's complement is shown to be a member of the compressed two's complement family where the compression factor (CF) is equal to one. The dynamic range of a compressed two's complement data format is shown to approach the dynamic range of a non compressed data format raised to the power of the CF. Improved performance for digital signal processing (DSP) applications such as digital filters and transforms is presented for specific instances of this family.

When a digital watermark is directly embedded into low frequency part of audio, sensitive noises maybe occur. In the paper, a method of audio digital watermark based on quantization index modulation is proposed to solve the problem. At first, audio signal is divided to fragment by audio mask effect. Then low frequency part of discrete wavelet transform (DWT) is extracted. Scrambling watermark is embedded into the low frequency part by quantization index modulation (QIM). The experiment results show that the presented method has a good capacity to fight many attacks.

The required bit resolution of digital-analog-converter (DAC) for optical OFDM was evaluated through simulation and experiment. We found that the signal degradation caused by quantization depends on the number of subcarriers theoretically, but the other noise generated in experiment suppresses the dependency. Additionally, signal degradation caused by quantization is independent of subcarrier modulation, and the performance improvement saturates with increasing bit resolution. With the criteria for the BER of 1 x 10- 3 , the required DAC resolution by simulation with ideal analog-digital-converter at receiver is 3 bits for QPSK, 4 bits for 8-QAM and 5 bits for 16-QAM and 32-QAM. From the experimental result, the required bit resolution is increased as 6 bits for 32-QAM.

In the field of audio watermarking, few schemes can resolve the problem of playback speed modification effectively. On the basis of statistical characteristic of DFT domain, a novel robust audio watermarking scheme against playback speed modification is proposed in this paper. Firstly, the original audio signal is segmented and then DFT is performed on each audio frame. Secondly, the absolute average value of DFT coefficients of each audio frame is computed and audio frames with distinct absolute average values are selected as watermark embedding regions. Thirdly, for one selected audio frame, it is divided into many segments, and the DFT domain relations among three neighboring segments are calculated and used to embed watermark bits. Finally, the watermark bits are repeatedly embedded into other selected audio frames. Experimental results show that the proposed scheme has acceptable imperceptibility and robustness against common audio signal processing attacks, including MP3 compression, re-quantization, re-sampling, etc. Furthermore, the ability of resisting playback speed modification and amplitude variation is also satisfactory.

A control-theoretic approach in designing Digital-to-Analogue Converters and Digital Amplifiers which leads to improved performance in Audio and Multimedia applications is presented in this paper. The design involves an over-sampling and a pulse modulation component which is driven by a pulse generation algorithm based on the characteristics of the output filter. The theoretical model results in a family of digital circuits whose operation is verified by computer simulations achieving a performance of Signal-to-Noise Ratio of 147 dB at a switching rate of 90 MHz. Implementation and hardware complexity issues are discussed based on a FPGA realization of the algorithm.

Aiming at content-based audio retrieval (CBAR) applications, a robust audio hashing scheme is proposed. First the audio is divided to frame by fixed length and then low-frequent and high-frequent components are obtained by three-level lifting-based wavelet transformation in every frame. Secondly the audio frame is approximately represented as a product of a base matrix and an encoding matrix, or coefficient matrix, using non-negative matrix factorization (NMF). Finally the sum of each column in the coefficient matrix is calculated, which is then quantized to produce one bit of the hash sequence. Experiment results show that the proposed scheme is robust against Mp3 compression, Real compression, filtering, amplitude compression, equalization, echo, etc. It is insensitive to small local change, and therefore is suitable for distinguishing different audios.

In this paper, we present an optimization framework for transmitting high quality audio sequences over error-prone wireless links. Our framework introduces apparatus and technique to optimally protect a stored audio sequence transmitted over a wireless link while considering the packetization overhead of audio frames. Utilizing rate compatible punctured Reed-Solomon (RS) codes and dynamic programming, it identifies the optimal assignment of parity to audio frames according to their perceptual importance such that the segmented SNR of the received audio sequence is maximized. Our framework covers two cases. In the first case, a frame grouping technique is proposed to packetize audio frames and protect them against temporarily correlated bit errors introduced by a fading wireless channel. In this case, each packet is treated as a channel coding codeword. In the second case, a one-dimensional RS coder is applied vertically to a sequence of horizontally formed packets associated with an audio sequence in order to protect the sequence against both bit errors introduced by fading wireless channels and packet erasures introduced by network buffering. Our numerical results capture the performance advantage of our framework compared to existing techniques proposed in the literature of audio transmission. We also note that our framework can be generically applied to a variety of audio coders, making it attractive in terms of implementation.

This paper deals with the application of adaptive signal models for parametric audio coding. A fully parametric audio coder, which decomposes the audio signal into sinusoids, transients and noise, is here proposed. Adaptive signal models for sinusoidal, transient, and noise modeling are therefore included in the parametric scheme in order to achieve high-quality and low bit-rate audio coding. In this paper, a new sinusoidal modeling method based on a perceptual distortion measure is proposed. For transient modeling, a fast and effective method based on matching pursuit with a mixed dictionary is chosen. The residue of the previous models is analyzed as a noise-like signal. The proposed parametric audio coder allows high quality audio coding for one-channel audio signals at 16 kbits/s (average bit rate). A bit-rate scalable version of the parametric audio coder is also proposed in this work. Bit-rate scalability is intended for audio streaming applications, which are highly demanded nowadays. The performance of the proposed parametric audio coders (nonscalable and scalable coders) is assessed in comparison to widely used audio coders operating at similar bit rates.

There have been many results on designing transceivers for MIMO channels. In early results, the transceiver is designed for a given bit allocation. In this paper we will jointly design the transceiver and bit allocation for maximizing bit rate. By using a high bit rate assumption, we will see that the optimal transceiver and bit allocation can be obtained in a closed form using simple Hadamard inequality and the Poincare separation theorem. In the simulation, we will demonstrate the usefulness of the joint design. Simulation results, in which a high bit rate assumption is not used in allocating bits, show that a higher bit rate can be achieved compared to previously reported methods.

In digital audio watermarking, the watermark's vulnerability to desynchronization attacks has long been a difficult problem. According to the audio statistics characteristics and synchronization code technique, a new robust audio watermarking scheme against desynchronization attacks is proposed in this paper. Firstly, the original digital audio is segmented and then each audio segment is cut into two parts. Secondly, with the spatial watermarking technique, the synchronization code is embedded into the statistics average value of audio samples in the first part. Finally, the second part of audio segment is cut into audio sections, the DWT is performed on the audio sections, and the watermark bit is embedded into the statistics average value of low frequency components. Experimental results show that the proposed scheme is inaudible and robust against common signals processing, including MP3 compression, low-pass filtering, noise addition, and equalization, etc. Moreover, it also survives several desynchronization attacks, such as random cropping, amplitude variation, pitch shifting, time-scale modification, and jittering, etc.

In this paper, a novel all-optical bit-error indicating scheme is numerically studied. The bit-error indicating function is achieved by two all-optical processing stages. Firstly, the amplified original bit stream propagates through a high-nonlinear fiber and experiences self-phase modulation which causes intensity-dependent spectrum broadening and split. And then, the bit stream output from the high-nonlinear fiber is filtered by a band-pass filter with the same central wavelength as the original bit stream to generate an error bit indicating signal. The error bit indicating signal, in which only the “Error” bits have the highest peak power, is synchronous with the delayed original bit stream. Therefore, the position of the “Error” bits in the original bit stream can be identified by setting only one judge threshold in the error bit indicating signal. The scheme is demonstrated for an 80 Gb/s bit stream with return-to-zero format by simulation. The results show that the scheme can be used for the all-optical bit-error indicating of the super high bit-rate systems using the return-to-zero format which is favored in the optical time division multiplexing transmission systems.

With the recent development of information technology and computer network, digital format of data has become more and more popular. However, a major problem faced by digital data providers and owners is protecting data from unauthorized copying and distribution. As a solution to the problem, digital watermark technology is now attracting attention as new method of protection against said unauthorized copying and distribution. The aim of the digital audio watermarking is to take prespecified data that carries certain information and hide it within the audio stream such that it is not audible to the human ear (i.e., transparent) but at the same time renders the file more resistant to removal (i.e., robust). In this paper, we propose a new method for embedding digital watermarks into audio signals in low frequency components, which method mitigates these and other related shortcomings. The proposed method uses the wavelet transform constructed by lifting-based wavelet transform (LBWT) in order to provide a fast implementation between watermark embedding and extraction parts. In the first stage of the proposed method, the original audio host signal is converted to a wavelet domain using LBWT. The signal is thus decomposed into low and high frequency components. Approximation coefficients correspond to low frequency components of the signal. Next, the watermark generated by pseudorandom numbers is embedded into wavelet approximation coefficients of the segmented host audio signal depending on the binary value of the binary image. The reason for embedding the watermark in the low frequency components is that these components' energy is greater than that of high frequency components in such a way that the watermark is inaudible; therefore, it should not alter the audible content and should not be easy to remove. The proposed method uses a binary image to decide whether or not the watermark generated by pseudorandom numbers is embedded in the audio host signal. To evaluate the performance of the proposed audio watermarking method, subjective and objective quality tests including bit error rate (BER) and signal-to-noise ratio (SNR) are conducted. The tests' results show that the proposed method yields a high recovery rate after attacks by commonly used audio data manipulations such as low-pass filtering, requantization, resampling and MP3 compression.