The document discusses different types of audio filters including low-pass, high-pass, band-pass, and notch (band-stop) filters. It provides examples of each filter type using Csound code, including applying filters to synthesized tones and noise to filter out specific frequencies. The document also demonstrates dynamically changing the center frequency and bandwidth of band-pass filters over time.
Overview:
Embedded systems increasingly employ a combination of low speed serial, analog voltages and RF communications which are tightly synchronized in time. This session will discuss the background of performing time and frequency domain analysis on these systems with example measurements on a digitally controlled RF transmitter.
What will you learn?
The challenges of debugging embedded systems
Frequency domain analysis and FFT basics
Time gating, Dynamic range and Triggering considerations
PLL locking measurement example
Originally presented at DesignCon 2013.
Jitter is a very important topic in signal integrity for high speed serial data links. The jitter performance of clock signals used in generating the serial data signal is critical to the overall performance of these signals.
Phase noise is the most sensitive and accurate measurement of the performance of precision clocks.
This presentation covers the theory and practice for making phase noise measurements on clock signals as well as the relationship between phase noise and total jitter, random jitter and deterministic jitter. Measurements on a typical clock signal is also included.
For more information, visit http://rohde-schwarz-scopes.com or call (888) 837-8772 to speak to a local Rohde & Schwarz expert.
Design and Implementation of Butterworth and Chebyshev Filters for Speech Signal Analysis
Link to the research paper:
https://research.ijcaonline.org/volume98/number7/pxc3897390.pdf
In the field of digital signal processing, the function of a filter is to remove unwanted parts of the signal such as random noise that is also undesirable. To remove noise from the speech signal transmission or to extract useful parts of the signal such as the components lying within a certain frequency range. Filters are broadly used in signal processing and communication systems in applications such as channel equalization, noise reduction, radar, audio processing, speech signal processing, video processing, biomedical signal processing that is noisy ECG, EEG, EMG signal filtering, electrical circuit analysis and analysis of economic and financial data.
Overview:
Embedded systems increasingly employ a combination of low speed serial, analog voltages and RF communications which are tightly synchronized in time. This session will discuss the background of performing time and frequency domain analysis on these systems with example measurements on a digitally controlled RF transmitter.
What will you learn?
The challenges of debugging embedded systems
Frequency domain analysis and FFT basics
Time gating, Dynamic range and Triggering considerations
PLL locking measurement example
Originally presented at DesignCon 2013.
Jitter is a very important topic in signal integrity for high speed serial data links. The jitter performance of clock signals used in generating the serial data signal is critical to the overall performance of these signals.
Phase noise is the most sensitive and accurate measurement of the performance of precision clocks.
This presentation covers the theory and practice for making phase noise measurements on clock signals as well as the relationship between phase noise and total jitter, random jitter and deterministic jitter. Measurements on a typical clock signal is also included.
For more information, visit http://rohde-schwarz-scopes.com or call (888) 837-8772 to speak to a local Rohde & Schwarz expert.
Design and Implementation of Butterworth and Chebyshev Filters for Speech Signal Analysis
Link to the research paper:
https://research.ijcaonline.org/volume98/number7/pxc3897390.pdf
In the field of digital signal processing, the function of a filter is to remove unwanted parts of the signal such as random noise that is also undesirable. To remove noise from the speech signal transmission or to extract useful parts of the signal such as the components lying within a certain frequency range. Filters are broadly used in signal processing and communication systems in applications such as channel equalization, noise reduction, radar, audio processing, speech signal processing, video processing, biomedical signal processing that is noisy ECG, EEG, EMG signal filtering, electrical circuit analysis and analysis of economic and financial data.
Embedded systems increasingly employ digital, analog and RF signals all of which are tightly synchronized in time. Debugging these systems is challenging in that one needs to measure a number of different signals in one or more domains (time, digital, frequency) and with tight time synchronization. This session will discuss how a digital oscilloscope can be used to effectively debug these systems, and some of the instrumentation considerations that go along with this.
Chebyshev filters are analog or digital filters having a steeper roll-off and more passband ripple (type I) or stop
band ripple (type II) than Butterworth filters. Chebyshev filters have the property that they minimize the error
between the idealized and the actual filter characteristic over the range of the filter,[citation needed] but with
ripples in the pass band. This type of filter is named after Pafnuty Chebyshev because its mathematical
characteristics are derived from Chebyshev polynomials.
Join us for a LIVE WEBINAR on this topic! Wednesday, November 14, 2:00pm ET
http://bit.ly/XPgjO7
Wide bandwidth modulation is becoming more common in communications. The emergence of the 802.11ac wireless Ethernet standard has extended the modulation bandwidth to 160 MHz which requires very wide band measurement equipment to measure. This presentation illustrates the details of a measurement method that uses a real time digital down converter and post processing software that measures the performance of this signal.
Embedded systems increasingly employ digital, analog and RF signals all of which are tightly synchronized in time. Debugging these systems is challenging in that one needs to measure a number of different signals in one or more domains (time, digital, frequency) and with tight time synchronization. This session will discuss how a digital oscilloscope can be used to effectively debug these systems, and some of the instrumentation considerations that go along with this.
Chebyshev filters are analog or digital filters having a steeper roll-off and more passband ripple (type I) or stop
band ripple (type II) than Butterworth filters. Chebyshev filters have the property that they minimize the error
between the idealized and the actual filter characteristic over the range of the filter,[citation needed] but with
ripples in the pass band. This type of filter is named after Pafnuty Chebyshev because its mathematical
characteristics are derived from Chebyshev polynomials.
Join us for a LIVE WEBINAR on this topic! Wednesday, November 14, 2:00pm ET
http://bit.ly/XPgjO7
Wide bandwidth modulation is becoming more common in communications. The emergence of the 802.11ac wireless Ethernet standard has extended the modulation bandwidth to 160 MHz which requires very wide band measurement equipment to measure. This presentation illustrates the details of a measurement method that uses a real time digital down converter and post processing software that measures the performance of this signal.
Introduction to operational Amplifier. For A2 level physics (CIE). Discusses characteristics of op amp, inverting and non inverting amplifier, and voltage follower, and transfer characetristics, virtual earth , etc
Fourier Transform : Its power and Limitations – Short Time Fourier Transform – The Gabor Transform - Discrete Time Fourier Transform and filter banks – Continuous Wavelet Transform – Wavelet Transform Ideal Case – Perfect Reconstruction Filter Banks and wavelets – Recursive multi-resolution decomposition – Haar Wavelet – Daubechies Wavelet.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
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Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
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The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
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Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
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The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
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SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
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Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
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Filters unit iii
1.
2. Filtering
• Filtering is another name for
subtractive synthesis
because it subtracts
frequencies from a sound
• Filtering is the opposite approach of
additive synthesis:
• Additive synthesis builds a complex sound
out of sine waves.
• Subtractive synthesis starts with a complex
source sound and removes some of the
frequency components.
4. Csound Filters
• Four Main Filter Types:
• Low-pass — tone
• High-pass — atone
• Band-pass — reson
• Notch (Band-stop) — areson
5. Low-Pass Filter
• Very common, probably about 50% of filters
used in computer music are low-pass.
Frequency Response Curve
• power = amp2; amp = sqrt(power)
• 1/2 power = sqrt(2)/2 amp = ~71% amp
6. Csound Low-Pass Filter (tone)
• synthesized oboe
[iv:15] original tone [iv:16] low-pass filter
261.6 Hertz at 523.2 Hz
8. High-Pass Filter
• Passes high frequencies, attenuates lows.
• Used to brighten a signal
• be careful, can also increase noise
• About 20% of filters used in computer music
are high-pass.
Frequency Response Curve
9. Csound High-Pass Filter (atone)
• synthesized oboe
[iv:15] original tone [iv:19] high-pass filter
261.6 Hertz at 1046.4 Hz
11. Band-Pass Filter
• Passes band of frequencies, attenuates those
above and below band.
• Most common in implementations of discrete
Fourier transform to separate out harmonics.
• About 20% of filters used in computer music
are band-pass.
Frequency Response Curve
12. Csound Band-Pass Filter (reson)
• Defined by center frequency f0, and bandwidth
of pass-band = fhighcutoff - flowcutoff
• synthesized oboe
[iv:15] original tone [iv:18] b-pass filter
261.6 Hertz at 523.2 Hz/10 bw
15. Band-Stop (Notch) Filter
• Stops band of frequencies, passes those
above and below band.
• Most common in removing electric hum (50
Hertz A/C).
• About 10% of filters used in computer music
are band-stop.
Frequency Response Curve
16. Csound Notch Filter (areson)
• Defined by center frequency f0, and bandwidth
of stop-band = fhighcutoff - flowcutoff
• pulse wave
[iv:21] original tone [iv:22] notch filter
261.6 Hertz at 1046.4 Hz
100 bw
17. Csound Notch Filter (areson)
• synthesized oboe with notch filter
; p2 p3 p4 p5 p6 p7 p8 p9
; start dur amp freq attk dec filtfr bw
i11 1 3.0 10000 261.6 .045 .15 1046.4 100
;ifiltfr=center freq of
afilt areson asig,ifiltfr,ibw,1 ;the stopband
afilt2 areson afilt,ifiltfr,ibw,1 ;steeper rolloff
abal balance afilt2, asig ;balance amplitude
• NOTE: The fourth argument in areson is
scaling — it must be 1 (0 default in Csound
manual doesn't work)
18. LP Filter
• original synthesized oboe tone 261.6
Hertz
[iv:15] 0. unfiltered tone [iv:26] 1. low-pass filter
523.2 Hz
19. HP and BP Filter
• original synthesized oboe tone 261.6
Hertz
[iv:27] 2. high-pass [iv:28] 3. band-pass
1046.4 Hz 1046.4 Hz
20. Dynamically Changing the Center
Frequency and Bandwidth
• original synthesized bassoon tone 69 Hz
• b-pass filter — freq from fundamental to harmonic 15
[iv:23] bassoon at 69 Hz [iv:24] bp filter 69-1035 Hz/bw 15
; p2 p3 p4 p5 p6 p7 p8 p9 p10 p11 p12 p13
; st dur amp frq attk dec flt1 flt2 bw1 bw2 wai gls
i15 1 3 9000 69 .23 .1 69 1035 15 15 .2 .6
21. Dynamically Changing the Center
Frequency and Bandwidth
• original synthesized bassoon tone 69 Hz
• band-pass filter — bw moving from 10 to 500
[iv:25] bp filter 276 Hz/bw 10-500 same — first 3 harmonics
; p2 p3 p4 p5 p6 p7 p8 p9 p10 p11 p12 p13
; st dur amp frq attk dec flt1 flt2 bw1 bw2 wai gls
i15 1 10 9000 69 .23 .1 276 276 10 500 .2 .6
22. Dynamically Changing the Center
Frequency and Bandwidth
• In the Csound manual:
ar tone asig, khp[,istor] ;l-pass
ar atone asig, khp[,istor] ;h-pass
ar reson asig, kcf,kbw[,iscale,istor] ;b-pass
ar areson asig, kcf,kbw[iscale,istor] ;notch
• Default is 0 for iscale and istor
• NOTE: Make sure that iscale is 1 if using
the areson notch filter, as Csound
doesn't work properly with the 0 default
23. Dynamically Changing the Center
Frequency and Bandwidth
• We can change the half-power, the center
frequency and the bandwidth at the k-rate
using linseg statements
• original synthesized bassoon tone 69 Hz
• b-pass filter — freq from fundamental to harmonic 15
kflfr linseg 69, idur, 1035 ;linseg for center
afilt reson asig,kflfr,ibw,0 ;freq of the passband
• band-pass filter — bandwidth moving from 10 to 500
kbw linseg 10, idur, 500 ; linseg for bandwidth
afilt reson asig,iflfr,kbw,0 ; of the passband
24. Dynamically Changing the Center
Frequency and Bandwidth
• a musical example: oboe, Bach, Fugue #2 in C Minor
• [iv:29] no filter
• [iv:30] lp filter, 55 -> 160 Hertz
• [iv:31] bp filter, 220 -> 7040 Hertz, bw 1
• [iv:32] bp filter, 220 -> 7040 Hertz, bw 1 -> 100
25. [iv:33] Hiss and Hum
compare with [iv:34] 60 Hertz sine wave
• hiss
• high frequency noise you hear on cassette tapes
• unfocused — not just a single frequency
• which kind of filter can you use to get rid of it?
• hum
• the noise you hear from machinery (such as lights
and computers)
• focused frequency, same as the local electrical
power
• which kind of filter can you use to get rid of it?
26. Filtered Noise
with Band-Pass Filters
[iv:35] noise with bp filter at 1046.4 Hz/bw 1% of filter freq
; p2 p3 p4 p5 p6 p7 p8
; start dur amp freq attk dec bw
i16 1 5 4000 1046.4 2 2.5 .01
27. Filtered Noise
with Band-Pass Filters
• [iv:36] a musical example: Ayers, Companion
of Strange Intimacies