Digital Signal Processing

Scientific & Technical

“Digital Signal Processing” No. 1-2013

In the issue:

- non-linear signal processing;
- power amplifier linearization;
- radio signal detection;
- wavelet transformation;
- image analysis;
- motion mask formation;
- adaptive filtering;
- phoneme recognition;
- active speech detection.

D.A. Lednov
Analyzing Hidden Trajectory Models (HTMs) of Vocal Tract Resonators for Phoneme Recognition System

Original works on phoneme recognition by Li Deng and his colleagues (Microsoft) published in 2000-2010 have been translated and are analyzed in the paper. The main trend of these publications is associated with developing the model for hidden trajectory parameters of vocal resonators. The development shows the functional relation of linear prediction coefficient dynamics to vocal tract resonator parameters having been smoothed by FIR-filter. Statistical model for the relation given is introduced and optimized. The model developed is completed with continuity equation to determine FIR-filter features for each phonetic state. The author also introduces an alternative optimization diagram to estimate parameters of a statistic model.
D.A. Lednov, e-mail:

Cascade Precompensator for Power Amplifier Linearization

Cascade structure of nonlinear digital precompensator being synthesized by a direct learning algorithm is proposed. Cascade precompensator including polynomial perception network and radially pruned Volterra model is proved to provide the most exact linearization for power amplifier with Wiener-Hammerstein model.
E.B.Solovyeva, e-mail:

K.A. Batenkov
Mathematical Modulator/Demodulator Models with Specified Nonlinearity Order

Mathematical modulator/demodulator models with a specified nonlinearity order based on functional series are synthesized. Signal processing complexity is estimated depending on the quantity of basis functions used.
K.A. Batenkov, e-mail:

D.A. Pimankin
Method of Weighted Least Squares for Image Analysis

A method of making a feature description for image areas based on analyzing image gradient vector orientations using a method of weighted least squares (WLSF method) is proposed. For a large class of images the method is sure to be a success in solving the problem of matching key points. The advantage of WLSF method compared to SURF method while analyzing noisy images is proved.
D.A. Pimankin, e-mail:

P.V. Kalinin, A.A. Sirota
Modeling Applicative Noise of Random Shape and with Various Opacity Degree

A generalized model for applicative noise on images as a set of local occlusions of random shape and with a various opacity degree is proposed. Variants to implement algorithms for modeling applicative noise and to control parameters of intensity, connectivity, opacity and shape irregularity degree are considered.
P.V. Kalinin, e-mail:
A.A. Sirota, e-mail:

E.I. Minakov, D.S. Kalistratov

Method of Constructing ALFA-mask

A method of constructing alfa-mask based on the principles of arithmetic context-dependent coding is considered. A method of constructing alfa-mask based on a dynamic regenerating for a movable part of the mask is proposed. Structural synthesis and comparative analysis for videocodec models using the above methods are performed.
E.I. Minakov, e-mail:

M.V. Samoilenko
Locating Radiation Sources and Measuring Their Powers by a Single Radar

A new method to locate spatial coordinates and measure powers of radiation sources using the measured output power of a receiving antenna by specific digital processing is presented. Mathematical statement of the above method and the results of computer-based experiments are given.
M.V. Samoilenko, e-mail:

A.Yu. Parshin, Yu.N. Parshin

Using Maximum Likelihood Estimations of Fractal Dimension in Non-Gaussian Statistics to Detect Radio Signals

The article deals with solving the problem of detecting objects by their radar images received from a radar station with a synthetic aperture based on their fractal properties. Maximum likelihood estimation for correlation dimension is proved to be a sufficient statistics for the above problem being solved. Fractal detector of radio signal is synthesized and analyzed using Gaussian statistics approximation and based on exponent distribution. Optimum energy-fractal complex detector is synthesized. Analytical expressions for detection characteristics are obtained.
A.Yu. Parshin, e-mail:
Yu.N. Parshin, e-mail:

O.V. Mandrikova, N.V. Glushkova, Yu.A. Polozov
Algorithms for Detecting and Analyzing Anomalies in Critical Frequency Parameters of Ionosphere (foF2) Based on Combining Wavelet Transformation and Autoregressive Models

A method of multicomponent modeling the ionosphere data based on combining wavelet transformation and autoregression models – integrated moving average to analyze and forecast data is presented. Features associated with solar activity and resulting from strong earthquakes in Kamchatka region are allocated. Algorithms to analyze ionosphere data based on discrete wavelet transformation for automatic allocation of ionosphere plasma anomalies and their parameter estimation are proposed. To assess the method and algorithms data of station “Paratunka” (Kamchatka) in 2001-2011 is used.
O.V. Mandrikova, e-mail:
N.V. Glushkova, e-mail:
Yu.A. Polozov, e-mail:

V.A Volchenkov, V.V. Vityazev

Methods and Algorithms for Detecting Voice Activity

Comparative analysis for the effectiveness of methods and algorithms to detect voice activity intervals and pauses between them is given. General information on standardized methods to detect voice activity is presented. The effectiveness of the methods is estimated. A new technique to detect pauses in voice activity is proposed.
V.A Volchenkov, e-mail:

N.V. Gudkova
Applying Principles of Digital Adaptive Filtering to Control a Dynamic Object with Unknown Mathematical Model

One of the methods to control continuous oscillatory objects with unknown mathematical model based on principles of direct and inverse adaptive modeling is considered. Two simultaneous adaptive processes for object control are formed in the system being investigated, namely the process of adaptive identification (direct object modeling) and the process of forming control effect (inverse modeling). Adaptive object models are realized as adaptive transversal filters with weights being estimated by least square method in real-time mode. Unlike traditional closed systems for automatic control there is no physical negative feedback between output and input in adaptive structure being considered; functional feedback being closed via adaptive process takes place instead. The methods being proposed enable to minimize the errors of control and damp oscillations as well as compensate random low frequency drift for the output signal of the object being controlled. The results of simulation system modeling prove the effectiveness of methods mentioned above.
N.V. Gudkova, e-mail:

D.V. Grigorenko, V.N. Ruchkin
Improving Cluster Neuroprocessor System Recoverability of Data Processing

Possible improving for cluster neuroprocessor system recoverability of pipeline, vector, pipeline-vector or vector-pipeline structure for data processing based on modern domestic NM640X microset is analyzed.
V.N. Ruchkin, e-mail:

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