ezmsg.sigproc#
Modules
Activation functions (ReLU, sigmoid, logit, etc.) applied element-wise. |
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Adaptive lattice notch filter for narrow-band interference removal. |
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Affine transformations via matrix multiplication: y = Ax or y = Ax + B. |
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Aggregation operations over arrays. |
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Convert AxisArray data to a target array backend. |
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Spectral band power estimation via windowed FFT and aggregation. |
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Backwards-compatible re-exports from ezmsg.baseproc. |
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Butterworth IIR filter design and application. |
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Streaming zero-phase Butterworth filter implemented as a two-stage composite processor. |
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Chebyshev Type I IIR filter design and application. |
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Comb filter for suppressing a fundamental frequency and its harmonics. |
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Coordinate space transformations for streaming data. |
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Decimation (downsample with anti-alias filtering). |
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Denormalize signals by applying random gains and offsets. |
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Remove linear or constant trends from data along an axis. |
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Compute differences along an axis. |
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Integer downsampling by selecting every Nth sample along an axis. |
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Exponentially weighted moving average (EWMA) utilities and parameter conversion. |
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Exponentially weighted moving average filter for streaming normalization. |
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Extract a named axis from an AxisArray as a standalone array. |
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Filter-bank canonical correlation analysis (FBCCA) for frequency detection. |
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Core IIR/FIR filtering infrastructure with BA and SOS coefficient support. |
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Parallel filterbank processing with convolution, FFT, or automatic mode selection. |
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Kaiser-window filterbank design with configurable bands and processing mode. |
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FIR Hilbert transform filter for analytic signal and envelope extraction. |
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Parks-McClellan (Remez) optimal equiripple FIR filter design and application. |
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FIR filter design and application using scipy.signal.firwin. |
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Gaussian kernel smoothing filter. |
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Kaiser window FIR filter design and application. |
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Apply a linear transformation: output = scale * input + offset. |
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Materialize (evaluate) lazy array data. |
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Time-aligned merge of two AxisArray streams along a non-time axis. |
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Deprecated message types; use |
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Quantize signal data to a fixed number of bits. |
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Resample signals to a target rate using interpolation. |
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Rolling z-score normalization using a sliding window of recent samples. |
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Triggered windowed sampling from a buffered signal stream. |
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Adaptive standard scaling using exponentially weighted moving statistics. |
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Inject synthetic sinusoidal signals into a data stream. |
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Time-domain single-band power estimation. |
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Select a subset of data along a named axis using slice notation. |
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Backwards-compatible re-exports from |
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Time-frequency spectrogram via windowed short-time Fourier transform. |
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FFT-based power spectrum estimation with configurable window functions. |
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Transpose or permute array dimensions. |
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Continuous wavelet transform (CWT) for streaming time-frequency analysis. |
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Sliding and tumbling window segmentation of streaming data. |